Biomarkers in ovarian cancer: To be or not to be

SYT7 as a Potential Prognostic Marker Promotes the Metastasis of Epithelial Ovarian Cancer Cells by Activating the STAT3 Pathway

The study aimed to investigate the impact of synaptotagmin 7 (SYT7) on the metastasis of epithelial ovarian cancer (EOC) and its potential mechanisms. This was achieved through the analysis of SYT7 expression levels and clinical relevance in EOC using bioinformatics analysis from TCGA. Additionally, the study examined the influence of SYT7 on the migration and invasion of EOC cells, as well as explored its molecular mechanisms using in vitro EOC cell lines and in vivo mouse xenograft models. Our research revealed that human EOC tissues exhibit significantly elevated levels of SYT7 compared to normal ovarian tissues, and that SYT7 expression is inversely correlated with overall survival. Suppression of SYT7 effectively impeded the migratory and invasive capabilities of CAOV3 cells, whereas overexpression of SYT7 notably accelerated tumor progression in A2780 cells. Mechanistic investigations demonstrated that SYT7 upregulates p-STAT3 and MMP2 in EOC cells. Importantly, treatment with the STAT3 inhibitor niclosamide effectively counteracted the oncogenic effects of SYT7 in EOC. The inhibition of SYT7 was found to significantly reduce in vivo tumor metastasis in a nude mouse xenograft model. Our findings suggest that the upregulation of SYT7 in EOC is associated with a negative prognosis, as it enhances tumor migration and invasion by activating the STAT3 signaling pathway. Thus, SYT7 might be utilized as a EOC prognostic marker and treatment target.

Fluorescent imaging probes for in vivo ovarian cancer targeted detection and surgery

Ovarian cancer is the most lethal gynecological cancer, with a survival rate of approximately 40% at five years from the diagno. The first-line treatment consists of cytoreductive surgery combined with chemotherapy (platinum- and taxane-based drugs). To date, the main prognostic factor is related to the complete surgical resection of tumor lesions, including occult micrometastases. The presence of minimal residual diseases not detected by visual inspection and palpation during surgery significantly increases the risk of disease relapse. Intraoperative fluorescence imaging systems have the potential to improve surgical outcomes. Fluorescent tracers administered to the patient may support surgeons for better real-time visualization of tumor lesions during cytoreductive procedures. In the last decade, consistent with the discovery of an increasing number of ovarian cancer-specific targets, a wide range of fluorescent agents were identified to be employed for intraoperatively detecting ovarian cancer. Here, we present a collection of fluorescent probes designed and developed for fluorescence-guided ovarian cancer surgery. Original articles published between 2011 and November 2022 focusing on fluorescent probes, currently under preclinical and clinical investigation, were searched in PubMed. The keywords used were targeted detection, ovarian cancer, fluorescent probe, near-infrared fluorescence, fluorescence-guided surgery, and intraoperative imaging. All identified papers were English-language full-text papers, and probes were classified based on the location of the biological target: intracellular, membrane, and extracellular.

METTL3/MALAT1/ELAVL1 Axis Promotes Tumor Growth in Ovarian Cancer

Background

Studies increasingly recognize the role of N6-methyladenosine (m6A) modification in cancer occurrence and development. METTL3 is a core catalytic subunit of m6A-modified methyltransferases complex, but its regulatory mechanism in ovarian cancer (OC) is not clear.

Methods

In this study, GEPIA 2.0 database was applied for expression analysis, survival analysis and correlation analysis for OC. Additionally, in vitro and in vivo assays were conducted to explore regulatory mechanisms of METTL3 in OC.

Results

We found that METTL3 and MALAT1 were significantly overexpressed in OC tissues and cells compared to normal ovarian tissues and cells. The proliferation rate of OC cells was reduced significantly after knocking down the expression of METTL3 or MALAT1. Subsequently, MALAT1 as oncogene was found to interact with METTL3 and was upregulated in OC tissues and cells. Silencing MALAT1 inhibited OC cell proliferation. Further studies indicated that METTL3 enhanced the stability of MALAT1 by promoting the m6A modification of MALAT1 and that ELAVL1 as a downstream binding protein significantly up-regulated MALAT1 expression.

Conclusion

In conclusion, METTL3 was a carcinogenic molecule that promoted the occurrence of OC. The potential mechanism of the carcinogenic effect of METTL3 was realized by enhancing the m6A modification of MALAT1 mRNA through RNA binding protein ELAVL1.

Assessing the Phenotype of a Homologous Recombination Deficiency Using High Resolution Array-Based Comparative Genome Hybridization in Ovarian Cancer

Ovarian cancer (OC) cells with homologous recombination deficiency (HRD) accumulate genomic scars (LST, TAI, and LOH) over a value of 42 in sum. PARP inhibitors can treat OC with HRD. The detection of HRD can be done directly by imaging these genomic scars, or indirectly by detecting mutations in the genes involved in HR. We show that HRD detection is also possible using high-resolution aCGH. A total of 30 OCs were analyzed retrospectively with high-resolution arrays as a test set and 19 OCs prospectively as a validation set. Mutation analysis was performed by HBOC TruRisk V2 panel to detect HR-relevant mutations. CNVs were clustered with respect to the involved HR genes versus the OC cases. In prospective validation, the HRD status determined by aCGH was compared with external HRD assessments. Two BRCA mutation carriers did not have HRD. OC could approximately differentiate into two groups with characteristic CNV patterns with different survival rates. Mutation frequencies have a linear regression on the HRD score. Mutations in individual HR-relevant genes do not always indicate HRD. This may depend on the mutation frequency in tumor cells. The aCGH shows the genomic scars of an HRD inexpensively and directly.

Unveiling the novel immune and molecular signatures of ovarian cancer: insights and innovations from single-cell sequencing

Ovarian cancer is a highly heterogeneous and lethal malignancy with limited treatment options. Over the past decade, single-cell sequencing has emerged as an advanced biological technology capable of decoding the landscape of ovarian cancer at the single-cell resolution. It operates at the level of genes, transcriptomes, proteins, epigenomes, and metabolisms, providing detailed information that is distinct from bulk sequencing methods, which only offer average data for specific lesions. Single-cell sequencing technology provides detailed insights into the immune and molecular mechanisms underlying tumor occurrence, development, drug resistance, and immune escape. These insights can guide the development of innovative diagnostic markers, therapeutic strategies, and prognostic indicators. Overall, this review provides a comprehensive summary of the diverse applications of single-cell sequencing in ovarian cancer. It encompasses the identification and characterization of novel cell subpopulations, the elucidation of tumor heterogeneity, the investigation of the tumor microenvironment, the analysis of mechanisms underlying metastasis, and the integration of innovative approaches such as organoid models and multi-omics analysis.

A tumor-infiltrating immune cells-related pseudogenes signature based on machine-learning predicts outcomes and immunotherapy responses in ovarian cancer

Previous researches have provided evidence for the significant involvement of pseudogenes in immune-related functions across different types of cancer. However, the mechanisms by which pseudogenes regulate immunity in ovarian cancer (OV) and their potential impact on clinical outcomes remain unclear. To address this gap in knowledge, our study utilized a novel computational framework to analyze a total of 491 samples from three public datasets. We employed a combination of 10 machine-learning algorithms to construct a signature known as the tumor-infiltrating immune cells-related pseudogenes signature (TIICPS). The TIICPS, consisting of 12 pseudogenes, demonstrated independent prognostic value for overall survival, surpassing conventional clinical traits, 62 published signatures, and TP53 and BRCA mutation status in three cohorts. Patients with low TIICPS exhibited heightened immune-related pathways, intricate genomic alterations, substantial immune infiltration, and greater potential for immunotherapy efficacy. Consequently, TIICPS holds promise as a predictive tool for prognosis and immunotherapy response in ovarian cancer.

Establishment and validation of an immune infiltration predictive model for ovarian cancer

BACKGROUND

The most prevalent mutation in ovarian cancer is the TP53 mutation, which impacts the development and prognosis of the disease. We looked at how the TP53 mutation associates the immunophenotype of ovarian cancer and the prognosis of the disease.

METHODS

We investigated the state of TP53 mutations and expression profiles in culturally diverse groups and datasets and developed an immune infiltration predictive model relying on immune-associated genes differently expressed between TP53 WT and TP53 MUT ovarian cancer cases. We aimed to construct an immune infiltration predictive model (IPM) to enhance the prognosis of ovarian cancer and investigate the impact of the IPM on the immunological microenvironment.

RESULTS

TP53 mutagenesis affected the expression of seventy-seven immune response-associated genes. An IPM was implemented and evaluated on ovarian cancer patients to distinguish individuals with low- and high-IPM subgroups of poor survival. For diagnostic and therapeutic use, a nomogram is thus created. According to pathway enrichment analysis, the pathways of the human immune response and immune function abnormalities were the most associated functions and pathways with the IPM genes. Furthermore, patients in the high-risk group showed low proportions of macrophages M1, activated NK cells, CD8+ T cells, and higher CTLA-4, PD-1, PD-L1, and TIM-3 than patients in the low-risk group.

CONCLUSIONS

The IPM model may identify high-risk patients and integrate other clinical parameters to predict their overall survival, suggesting it is a potential methodology for optimizing ovarian cancer prognosis.

The role of OIP5 in the carcinogenesis and progression of ovarian cancer

BACKGROUND

Opa interacting protein 5 (OIP5), which is a cancer/testis-specific gene, plays a cancer-promoting role in various types of human cancer. However, the role of OIP5 in the carcinogenesis and progression of ovarian cancer remains unknown.

METHODS

We first analyzed the expression of OIP5 in ovarian cancer and various human tumors with the Sangerbox online analysis tool. GSE12470, GSE14407 and GSE54388 were downloaded from the Gene Expression Omnibus (GEO) database, and GEO2R was used to screen differentially expressed genes in ovarian cancer tissues. Gene Ontology (GO) enrichment analysis was used to explore the related biological processes. Receiver operating characteristic (ROC) curve was generated to evaluate the predictive ability of OIP5 for ovarian cancer. Next, RT-PCR, immunohistochemistry and Western blotting were utilized to evaluate the expression of OIP5 in ovarian cancer. CCK8, EdU proliferation assays and colony formation assays were used to measure cell proliferation, cell cycle progression was examined by PI staining and flow cytometry, and cell apoptosis was examined by Caspase3/7 activity assays. The effect of OIP5 on the migration and invasion of ovarian cancer cells was analyzed with Transwell assays.

RESULTS

We found that OIP5 is highly expressed in ovarian cancer through bioinformatics analysis, and importantly, OIP5 may be an important biomarker for the prognosis and diagnosis of ovarian cancer. RT-PCR assays, immunohistochemistry and Western blotting were also used to confirm the high expression of OIP5 in ovarian cancer. Subsequently, we demonstrated that the proliferation and migration of the ovarian cancer cell line A2780 were significantly inhibited after OIP5 gene silencing, apoptosis was increased and cell cycle progression was arrested at the G1 phase.

CONCLUSION

This study indicated that OIP5 was highly expressed in ovarian cancer and that downregulation of OIP5 inhibited the proliferation, migration and invasion of ovarian cancer cells, induced cell cycle arrest and promoted cell apoptosis. Therefore, OIP5 may be an important biomarker for the early diagnosis and potential target for treatment of ovarian cancer.

In Vivo Ultrasound Molecular Imaging in the Evaluation of Complex Ovarian Masses: A Practical Guide to Correlation with Ex Vivo Immunohistochemistry

Ovarian cancer is the fifth leading cause of cancer-related deaths in women and the most lethal gynecologic cancer. It is curable when discovered at an early stage, but usually remains asymptomatic until advanced stages. It is crucial to diagnose the disease before it metastasizes to distant organs for optimal patient management. Conventional transvaginal ultrasound imaging offers limited sensitivity and specificity in the ovarian cancer detection. With molecularly targeted ligands addressing targets, such as kinase insert domain receptor (KDR), attached to contrast microbubbles, ultrasound molecular imaging (USMI) can be used to detect, characterize and monitor ovarian cancer at a molecular level. In this article, the authors propose a standardized protocol is proposed for the accurate correlation between in- vivo transvaginal KDR-targeted USMI and ex vivo histology and immunohistochemistry in clinical translational studies. The detailed procedures of in vivo USMI and ex vivo immunohistochemistry are described for four molecular markers, CD31 and KDR with a focus on how to enable the accurate correlation between in vivo imaging findings and ex vivo expression of the molecular markers, even if not the entire tumor could can be imaged by USMI, which is not an uncommon scenario in clinical translational studies. This work aims to enhance the workflow and the accuracy of characterization of ovarian masses on transvaginal USMI using histology and immunohistochemistry as reference standards, which involves sonographers, radiologists, surgeons, and pathologists in a highly collaborative research effort of USMI in cancer.

A systematic review and meta-analysis of CT and MRI radiomics in ovarian cancer: methodological issues and clinical utility

OBJECTIVES

We aimed to present the state of the art of CT- and MRI-based radiomics in the context of ovarian cancer (OC), with a focus on the methodological quality of these studies and the clinical utility of these proposed radiomics models.

METHODS

Original articles investigating radiomics in OC published in PubMed, Embase, Web of Science, and the Cochrane Library between January 1, 2002, and January 6, 2023, were extracted. The methodological quality was evaluated using the radiomics quality score (RQS) and Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2). Pairwise correlation analyses were performed to compare the methodological quality, baseline information, and performance metrics. Additional meta-analyses of studies exploring differential diagnoses and prognostic prediction in patients with OC were performed separately.

RESULTS

Fifty-seven studies encompassing 11,693 patients were included. The mean RQS was 30.7% (range - 4 to 22); less than 25% of studies had a high risk of bias and applicability concerns in each domain of QUADAS-2. A high RQS was significantly associated with a low QUADAS-2 risk and recent publication year. Significantly higher performance metrics were observed in studies examining differential diagnosis; 16 such studies as well as 13 exploring prognostic prediction were included in a separate meta-analysis, which revealed diagnostic odds ratios of 25.76 (95% confidence interval (CI) 13.50-49.13) and 12.55 (95% CI 8.38-18.77), respectively.

CONCLUSION

Current evidence suggests that the methodological quality of OC-related radiomics studies is unsatisfactory. Radiomics analysis based on CT and MRI showed promising results in terms of differential diagnosis and prognostic prediction.

CRITICAL RELEVANCE STATEMENT

Radiomics analysis has potential clinical utility; however, shortcomings persist in existing studies in terms of reproducibility. We suggest that future radiomics studies should be more standardized to better bridge the gap between concepts and clinical applications.

Identification of STEAP3-based molecular subtype and risk model in ovarian cancer

BACKGROUND

Ovarian cancer (OC) is one of the most common malignancies in women. It has a poor prognosis owing to its recurrence and metastasis. Unfortunately, reliable markers for early diagnosis and prognosis of OC are lacking. Our research aimed to investigate the value of the six-transmembrane epithelial antigen of prostate family member 3 (STEAP3) as a prognostic predictor and therapeutic target in OC using bioinformatics analysis.

METHODS

STEAP3 expression and clinical data were acquired from The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), and Gene Expression Omnibus (GEO). Unsupervised clustering was used to identify molecular subtypes. Prognosis, tumor immune microenvironment (TIME), stemness indexes, and functional enrichment analysis were compared between two definite clusters. Through the least absolute shrinkage and selection operator (LASSO) regression analysis, a STEAP3-based risk model was developed, and the predictive effectiveness of this signature was confirmed using GEO datasets. A nomogram was used to predict the survival possibility of patients. Additionally, TIME, tumor immune dysfunction and exclusion (TIDE), stemness indexes, somatic mutations, and drug sensitivity were evaluated in different risk groups with OC. STEAP3 protein expression was detected using immunohistochemistry (IHC).

RESULTS

STEAP3 displayed marked overexpression in OC. STEAP3 is an independent risk factor for OC. Based on the mRNA levels of STEAP3-related genes (SRGs), two distinct clusters were identified. Patients in the cluster 2 (C2) subgroup had a considerably worse prognosis, higher immune cell infiltration, and lower stemness scores. Pathways involved in tumorigenesis and immunity were highly enriched in the C2 subgroup. A prognostic model based on 13 SRGs was further developed. Kaplan-Meier analysis indicated that the overall survival (OS) of high-risk patients was poor. The risk score was significantly associated with TIME, TIDE, stemness indexes, tumor mutation burden (TMB), immunotherapy response, and drug sensitivity. Finally, IHC revealed that STEAP3 protein expression was noticeably elevated in OC, and overexpression of STEAP3 predicted poor OS and relapse-free survival (RFS) of patients.

CONCLUSION

In summary, this study revealed that STEAP3 reliably predicts patient prognosis and provides novel ideas for OC immunotherapy.

Adnexal Lesion Imaging: Past, Present, and Future

Currently, imaging is part of the standard of care for patients with adnexal lesions prior to definitive management. Imaging can identify a physiologic finding or classic benign lesion that can be followed up conservatively. When one of these entities is not present, imaging is used to determine the probability of ovarian cancer prior to surgical consultation. Since the inclusion of imaging in the evaluation of adnexal lesions in the 1970s, the rate of surgery for benign lesions has decreased. More recently, data-driven Ovarian-Adnexal Reporting and Data System (O-RADS) scoring systems for US and MRI with standardized lexicons have been developed to allow for assignment of a cancer risk score, with the goal of further decreasing unnecessary interventions while expediting the care of patients with ovarian cancer. US is used as the initial modality for the assessment of adnexal lesions, while MRI is used when there is a clinical need for increased specificity and positive predictive value for the diagnosis of cancer. This article will review how the treatment of adnexal lesions has changed due to imaging over the decades; the current data supporting the use of US, CT, and MRI to determine the likelihood of cancer; and future directions of adnexal imaging for the early detection of ovarian cancer.

Inflammation Control and Tumor Growth Inhibition of Ovarian Cancer by Targeting Adhesion Molecules of E-Selectin

Objective: The aim is to use E-selectin-binding peptide (ESBP) to actively recognize E-selectin, so allowing a drug delivery system to actively recognize the cells and inhibit the tumor growth of ovarian cancer by targeting adhesion molecules of E-selectin. An ovarian-cancer-directed drug delivery system was designed based on the high affinity of E-selectin-binding peptide (ESBP) to E-selectin. The effects and mechanisms of ESBP-bovine serum albumin (BSA) polymerized nanoparticles were investigated. Methods: BSA polymerized nanoparticles (BSANPs) and ESBP-BSANPs-paclitaxel (PTX) were prepared and their characteristics were measured. The in vitro targetability and cytotoxicity of ESBP-BSANPs-PTX were evaluated through in vitro drug uptake and MTT experiments. The mechanisms of ESBP-BSANPs-PTX were investigated via apoptosis, wound healing and immunohistochemistry assays. The in vivo targeting properties and drug effects were observed in a mouse tumor-bearing model. Results: In vitro experiments revealed an increase in the uptake of ESBP-BSANPs-FITC. The cytotoxicity of ESBP-BSANPs-PTX in A2780/CP70, HUVEC, RAW264.7 and ID8 cells was higher than that of PTX alone. ESBP-BSANPs-PTX increased cell apoptosis in a dose-dependent manner and exhibited a greater ability to inhibit cell migration than BSANPs-PTX. In vivo experiments demonstrated the targetability and good effects of ESBP-BSANPs. Conclusions: ESBP-BSANPs-PTX improve PTX targetability, provide tumor-specific and potent therapeutic activities, and show promise for the development of agents in preclinical epithelial ovarian cancer.

Paxillin is a potential prognostic biomarker associated with immune cell infiltration in ovarian cancer

Objective

To investigate the expression, prognosis, and underlying mechanism of Paxillin (PXN) in ovarian cancer.

Materials and methods

By comprehensive use of various bioinformatics tools, we analyzed the expression of PXN and its prognostic value in ovarian cancer. Then, the enrichment analyses were conducted to determine the possible regulatory pathways PXN involved in ovarian cancer. Finally, the associations of PXN expression with immune cell infiltration and immune checkpoints were analyzed.

Results

PXN was highly expressed in ovarian cancer and its expression could independently predict the overall survival of ovarian cancer patients. More importantly, PXN had a superior ability in predicting long-term survival than age and tumor residual disease in ovarian cancer patients. In addition, PXN was positively related to adherens junction and tight junction pathways. Significant negative relationships between PXN expression and immune infiltrates were observed, however, PXN was positively connected with immune checkpoint (VSIR) in ovarian cancer.

Conclusions

PXN serves as a reliable prognostic biomarker and may be a potent therapeutic target for ovarian cancer. Moreover, high PXN expression may affect ovarian cancer progression via positive regulation of metastasis-related pathways.

New insights into the role of circular RNAs in ovarian cancer

Ovarian cancer (OC) is one of the most aggressive tumors in women and has a poor prognosis and the highest mortality rate. Circular RNAs (circRNAs) are a type of endogenous non-coding RNAs that have recently attracted interest in cancer research. Increasing evidence has demonstrated that circRNAs play an oncogenic or suppressive role in tumorigenesis and progression, and show tissue- or developmental-stage-specific expression. Due to high stability, conservation, abundance, and specificity, circRNAs are considered promising biomarkers for the diagnosis and prognosis of cancer. Herein, we have summarized the expression profiles of circRNAs in OC tissues, serums, and cell lines. Moreover, we discuss how circRNAs participate in the regulation of multiple biological processes in OC, including cell proliferation, apoptosis, migration, invasion, autophagy, epithelial-to-mesenchymal transition, glucose metabolism, angiogenesis, immune response, and chemotherapy resistance, by sponging microRNAs and interacting with proteins.

A novel tumor mutational burden-based risk model predicts prognosis and correlates with immune infiltration in ovarian cancer

Tumor mutational burden (TMB) has been reported to determine the response to immunotherapy, thus affecting the patient’s prognosis in many cancers. However, it is unclear whether TMB or TMB-related signature could be used as prognostic indicators for ovarian cancer (OC), as its potential association with immune infiltration remains poorly understood. Therefore, this study aimed to develop a novel TMB-related risk model (TMBrisk) to predict the prognosis of OC patients on the basis of exploring TMB-related genes, and to explore the potential association between TMB/TMBrisk and immune infiltration. The mutational landscape, TMB scores, and correlations between TMB and clinical characteristics and immune infiltration were investigated in The Cancer Genome Atlas (TCGA)-OV cohort. Differentially expressed gene (DEG) analyses and weighted gene co-expression network analysis (WGCNA) were performed to derive TMB-related genes. TMBrisk was constructed by Cox regression and further validated in Gene Expression Omnibus (GEO) datasets. The mRNA and protein expression levels and biological functions of TMBrisk hub genes were verified through Gene Expression Profiling Interactive Analysis (GEPIA), GSCA Lite, the Human Protein Atlas (HPA) database, and RT-qPCR. TMBrisk-related biological phenotypes were analyzed in function enrichment and tumor immune infiltration signature. Potential therapeutic regimens were inferred utilizing the Genomics of Drug Sensitivity in Cancer (GDSC) database and connectivity map (CMap). According to our results, higher TMB was associated with better survival and higher CD8+ T cell, regulatory T cell, and NK cell infiltration. TMBrisk was developed based on CBWD1, ST7L, RFX5-AS1, C3orf38, LRFN1, LEMD1, and HMGB1. High TMBrisk was identified as a poor factor for prognosis in TCGA and GEO datasets; the high-TMBrisk group comprised more higher-grade (G2 and G3) and advanced clinical stage (stage III/IV) tumors. Meanwhile, higher TMBrisk was associated with an immunosuppressive phenotype, with less infiltration of a majority of immunocytes and less expression of several genes of the human leukocyte antigen (HLA) family. Moreover, a nomogram containing TMBrisk showed a strong predictive ability demonstrated by time-dependent ROC analysis. Overall, this novel TMB-related risk model (TMBrisk) could predict prognosis, evaluate immune infiltration, and discover new therapeutic regimens in OC, which is very promising in clinical promotion.

Anticancer Effect of Puerarin on Ovarian Cancer Progression Contributes to the Tumor Suppressor Gene Expression and Gut Microbiota Modulation

Ovarian cancer (OC) causes more deaths than any other cancer of the female reproductive system due to its late presentation and malignant nature. Although significant progress has been made in the diagnosis and treatment of OC over the last decade, chemotherapeutic drug resistance and cancer recurrence remain serious challenges in OC management. In the field of cancer therapy, traditional Chinese herbal medicines and their active compounds have been widely reported to have favorable therapeutic effects on cancer. Recent studies have also revealed the protective effect of puerarin in cancer, but the exact role and underlying mechanism of puerarin in OC remain unclear. Here, we established in vivo and in vitro OC models to evaluate the anticancer effect of puerarin. It was found that puerarin significantly inhibited OC cell viability and proliferation and induced cell apoptosis. In OC model mice, puerarin treatment suppressed tumor formation and modulated the gut microbiome. In addition, the expression of tumor suppressor genes was activated by puerarin in vitro and in vivo. These findings add to the existing knowledge on the usefulness of herbal active ingredients for the prevention and treatment of OC and provide a new perspective regarding the therapeutic potential of puerarin in cancer.

The Expression and Role Analysis of Methylation-Regulated Differentially Expressed Gene UBE2C in Pan-Cancer, Especially for HGSOC

Simple Summary

DNA methylation has attracted a great deal of scientific interest as an early biomarker and potential therapeutic target. HGSOC result in high mortality due to the absence of reliable biomarkers for early diagnosis and prognosis. In this study, we performed an integrated bioinformatic analysis and found that UBE2C was hypomethylation and overexpression in ovarian cancer, which was associated with advanced cancer stages and poor prognoses. Meantime, this finding was also confirmed in pan-cancer analysis. Furthermore, the experimental validation of the expression and role of UBE2C was performed on HGSOC tissues and cancer cell lines. Importantly, demethylation could upregulate the expression of UBE2C. Taken together, methylation-regulated UBE2C may be a novel biomarker for diagnosis and prognosis, not only for ovarian cancer but a variety of cancers.

Abstract

High-grade serous ovarian cancer (HGSOC) is the most fatal gynecological malignant tumor. DNA methylation is associated with the occurrence and development of a variety of tumor types, including HGSOC. However, the signatures regarding DNA methylation changes for HGSOC diagnosis and prognosis are less explored. Here, we screened differentially methylated genes and differentially expressed genes in HGSOC through the GEO database. We identified that UBE2C was hypomethylation and overexpression in ovarian cancer, which was associated with more advanced cancer stages and poor prognoses. Additionally, the pan-cancer analysis showed that UBE2C was overexpressed and hypomethylation in almost all cancer types and was related to poor prognoses for various cancers. Next, we established a risk or prognosis model related to UBE2C methylation sites and screened out the three sites (cg03969725, cg02838589, and cg00242976). Furthermore, we experimentally validated the overexpression of UBE2C in HGSOC clinical samples and ovarian cell lines using quantitative real-time PCR, Western blot, and immunohistochemistry. Importantly, we discovered that ovarian cancer cell lines had lower DNA methylation levels of UBE2C than IOSE-80 cells (normal ovarian epithelial cell line) by bisulfite sequencing PCR. Consistently, treatment with 5-Azacytidine (a methylation inhibitor) was able to restore the expression of UBE2C. Taken together, our study may help us to understand the underlying molecular mechanism of UBE2C in pan-cancer tumorigenesis; it may be a useful biomarker for diagnosis, treatment, and monitoring, not only of ovarian cancer but a variety of cancers.

Biological Role of Tumor/Stromal CXCR4-CXCL12-CXCR7 in MITO16A/MaNGO-OV2 Advanced Ovarian Cancer Patients

Simple Summary

Despite rapid progress in the research on epithelial ovarian cancer (EOC), it is usually diagnosed during the advanced stage with only 30% of patients surviving longer than 5 years. This is the first study in which the whole CXCR4-CXCL12-CXCR7 axis was systematically evaluated in tumor and stromal cells, through rigorous statistical methods in a prospective clinical trial. CXCL12 expression in cancer cells is associated with worse progression-free survival in stage III EOC patients, and deserves further attention as a potential prognostic and therapeutic target.

Abstract

This study investigated the prognostic role of the CXCR4-CXCL12-CXCR7 axis in advanced epithelial ovarian cancer (EOC) patients receiving first-line treatment within the MITO16A/MaNGO-OV2 phase-IV trial. CXCR4-CXCL12-CXCR7 expression was evaluated in the epithelial and stromal component of 308 EOC IHC-stained tumor samples. The statistical analysis focused on biomarkers’ expression, their association with other variables and prognostic value. Zero-inflated tests, shrinkage, bootstrap procedures, and multivariable models were applied. The majority of EOC (75.0%) expressed CXCR4 and CXCR7, 56.5% expressed the entire CXCR4-CXCL12-CXCR7 axis, while only 4.6% were negative for CXCL12 and its cognate receptors, in regard to the epithelial component. Stromal CXCL12 and CXCR7, expressed in 11.2% and 65.5%, respectively, were associated with the FIGO stage. High CXCL12 in epithelial cancer cells was associated with shorter progression-free and overall survival. However, after adjusting for overfitting due to best cut-off multiplicity testing, the significance was lost. This is a wide-ranging, prospective study in which CXCR4-CXCL12-CXCR7 were systematically evaluated in epithelial and stromal components, in selected stage III-IV EOC. Although CXCL12 was not prognostic, epithelial expression identified high-risk FIGO stage III patients for PFS. These data suggest that it might be worth studying the CXCL12 axis as a therapeutic target to improve treatment efficacy in EOC patients.

A combined biomarker panel shows improved sensitivity and specificity for detection of ovarian cancer

Background

Combined biomarkers can improve the sensitivity and specificity of ovarian cancer (OC) diagnosis and effectively predict patient prognosis. This study explored the diagnostic and prognostic values of serum CCL18 and CXCL1 antigens combined with C1D, FXR1, ZNF573, and TM4SF1 autoantibodies in OC.

Methods

CCL18 and CXCL1 monoclonal antibodies and C1D, FXR1, ZNF573, and TM4SF1 antigens were coated with microspheres. Logistic regression was used to construct a serum antigen‐antibody combined detection model; receiver‐operating characteristic curve (ROC) was used to evaluate the diagnostic efficacy of the model; and the Kaplan‐Meier method and Cox regression models were used for survival analysis to evaluate the prognosis of OC. Data from The Cancer Genome Atlas (TCGA) and Genotype‐Tissue Expression (GTEx) projects and online survival analysis tools were used to evaluate prognostic genes for OC. The CIBERSORT immune score was used to explore the factors influencing prognosis and their relationship with tumor‐infiltrating immune cells.

Results

The levels of each index in the blood samples of patients with OC were higher than those of the other groups. The combined detection model has higher specificity and sensitivity in the diagnosis of OC, and its diagnostic efficiency is better than that of CA125 alone and diagnosing other malignant tumors. CCL18 and TM4SF1 may be factors affecting the prognosis of OC, and CCL18 may be related to immune‐infiltrating cells.

Conclusions

The serum antigen‐antibody combined detection model established in this study has high sensitivity and specificity for the diagnosis of OC.

Plasma circN4BP2L2 is a promising novel diagnostic biomarker for epithelial ovarian cancer

BACKGROUND

Circular RNAs (circRNAs) are more stable than linear RNA molecules, which makes them promising diagnostic biomarkers for diseases. By circRNA-sequencing analysis, we previously found that circN4BP2L2 was significantly decreased in epithelial ovarian cancer (EOC) tissues, and was predictive of disease progression. The aim of this study was to evaluate the diagnostic value of plasma circN4BP2L2 in EOC.

METHODS

Three hundred seventy-eight plasma samples were acquired prior to surgery. Samples were obtained from 126 EOC patients, 126 benign ovarian cyst patients, and 126 healthy volunteers. CircN4BP2L2 was assessed using reverse transcription-quantitative polymerase chain reaction (RT-qPCR). Cancer antigen 125 (CA125) and human epididymis protein 4 (HE4) were assessed using enzyme-linked immunosorbent assay (ELISA). EOC cells were transfected with small interference RNAs (siRNAs) and cell proliferation, migration, invasion, cell cycle and cell apoptosis were performed to assess the effect of circN4BP2L2 in EOC. Receiver operating curve (ROC), the area under the curve (AUC), sensitivity and specificity were estimated.

RESULTS

Plasma circN4BP2L2 was significantly downregulated in EOC patients. Decreased circN4BP2L2 was significantly associated with advanced tumor stage, worse histological grade, lymph node metastasis and distant metastasis in EOC. CircN4BP2L2 inhibited tumor cell migration and invasion in vitro. CircN4BP2L2 could significantly separate EOC from benign (AUC = 0.82, P <  0.01) or normal (AUC = 0.90, P <  0.01) cohort. Early stage EOC vs benign (AUC = 0.81, P <  0.01) or normal (AUC = 0.90, P <  0.01) cohort could also be distinguished by circN4BP2L2. In discrimination between EOC cohort and benign or normal cohort, circN4BP2L2 performed equally well in both pre- and post-menopausal women. The combination of circN4BP2L2, CA125 and HE4 showed high sensitivity and specificity in detecting EOC cases.

CONCLUSIONS

Plasma circN4BP2L2 is significantly downregulated in EOC and might serve as a promising novel diagnostic biomarker for EOC patients, especially in early stage EOC cases. CircN4BP2L2 might act as an adjunct to CA125 and HE4 in detecting EOC. Further large-scale studies are warranted to verify our results.

Role of Mitochondria in Interplay between NGF/TRKA, miR-145 and Possible Therapeutic Strategies for Epithelial Ovarian Cancer

Ovarian cancer is the most lethal gynecological neoplasm, and epithelial ovarian cancer (EOC) accounts for 90% of ovarian malignancies. The 5-year survival is less than 45%, and, unlike other types of cancer, the proportion of women who die from this disease has not improved in recent decades. Nerve growth factor (NGF) and tropomyosin kinase A (TRKA), its high-affinity receptor, play a crucial role in pathogenesis through cell proliferation, angiogenesis, invasion, and migration. NGF/TRKA increase their expression during the progression of EOC by upregulation of oncogenic proteins as vascular endothelial growth factor (VEGF) and c-Myc. Otherwise, the expression of most oncoproteins is regulated by microRNAs (miRs). Our laboratory group reported that the tumoral effect of NGF/TRKA depends on the regulation of miR-145 levels in EOC. Currently, mitochondria have been proposed as new therapeutic targets to activate the apoptotic pathway in the cancer cell. The mitochondria are involved in a myriad of functions as energy production, redox control, homeostasis of Ca⁺², and cell death. We demonstrated that NGF stimulation produces an augment in the Bcl-2/BAX ratio, which supports the anti-apoptotic effects of NGF in EOC cells. The review aimed to discuss the role of mitochondria in the interplay between NGF/TRKA and miR-145 and possible therapeutic strategies that may decrease mortality due to EOC.

The Identification of RNA Modification Gene PUS7 as a Potential Biomarker of Ovarian Cancer

RNA modifications are reversible, dynamically regulated, and involved in a variety of diseases such as cancers. Given the lack of efficient and reliable biomarkers for early diagnosis of ovarian cancer (OV), this study was designed to explore the role of RNA modification genes (RMGs) in the diagnosis of OV. Herein, 132 RMGs were retrieved in PubMed, 638 OV and 18 normal ovary samples were retrieved in The Cancer Genome Atlas (TCGA), and GSE18520 cohorts were collected for differential analysis. Finally, PUS7 (Pseudouridine Synthase 7) as differentially expressed RMGs (DEGs-RMGs) was identified as a diagnostic biomarker candidate and evaluated for its specificity and sensitivity using Receiver Operating Characteristic (ROC) analysis in TCGA and GEO data. The protein expression, mutation, protein interaction networks, correlated genes, related pathways, biological processes, cell components, and molecular functions of PUS7 were analyzed as well. The upregulation of PUS7 protein in OV was confirmed by the staining images in HPA and tissue arrays. Collectively, the findings of the present study point towards the potential of PUS7 as a diagnostic marker and therapeutic target for ovarian cancer.

Clinical significance for combined coagulation indexes in epithelial ovarian cancer prognosis

Background

Increasing evidence supported an association between cancer and coagulation system. We aimed to identify prognostic values of coagulation biomarkers in epithelial ovarian cancer (EOC).

Methods

A retrospective study was conducted on patients who underwent optimal tumor debulking followed by platinum-based chemotherapy at our institution. The predictive value of coagulation variables was evaluated by receiver operating characteristic (ROC) curves. Through Cox hazards regression models, prognostic factors were determined for recurrence-free survival (RFS) and overall survival (OS). Survival curves were visualized by Kaplan–Meier method and compared through Log-rank analysis.

Results

We involved 482 EOC patients and followed up for 64 (range, 36–87) months. According to ROC curves, D-dimer and International normalized ratio (INR) had superior predictive value than other coagulation indexes, with area under curve (AUC) of 0.758 and 0.742. Patients were then stratified into three combined D-dimer and INR (DD-INR) groups based on the cut-off value of 0.97 mg/L and 0.86, respectively. Through regression analysis, we demonstrated that age (HR 1.273; 95%CI 1.048–2.047; p = 0.045), pathological grade (HR 1.419; 95% CI 1.102–2.491; p = 0.032), clinical stage (HR 2.038; 95%CI 1.284–3.768; p = 0.008), CA-125 (HR 1.426; 95%CI 1.103–1.894; p = 0.038) and DD-INR (HR 2.412; 95%CI 1.683–3.241; p = 0.009) were independent prognostic factors. Survival analysis showed that patients with higher DD-INR experienced poor survival (p = 0.0013 for RFS and p = 0.0068 for OS). Further subgroup analysis revealed that evaluated DD-INR was significantly associated with poor survival among patients with advanced stage (p = 0.0028 for RFS and p = 0.0180 for OS).

Conclusion

Our findings suggested that coagulation indexes, especially the combined DD-INR were promising biomarkers for prognosis stratification in EOC patients, especially those with advanced clinical stages.

Potential Role of Diabetes Mellitus-Associated T Cell Senescence in Epithelial Ovarian Cancer Omental Metastasis

Epithelial ovarian cancer (EOC) is one of the most common causes of cancer-related deaths among women and is associated with age and age-related diseases. With increasing evidence of risks associated with metabolic inflammatory conditions, such as obesity and type 2 diabetes mellitus (T2DM), it is important to understand the complex pathophysiological mechanisms underlying cancer progression and metastasis. Age-related conditions can lead to both genotypic and phenotypic immune function alterations, such as induction of senescence, which can contribute to disease progression. Immune senescence is a common phenomenon in the ageing population, which is now known to play a role in multiple diseases, often detrimentally. EOC progression and metastasis, with the highest rates in the 75-79 age group in women, have been shown to be influenced by immune cells within the "milky spots" or immune clusters of the omentum. As T2DM has been reported to cause T cell senescence in both prediabetic and diabetic patients, there is a possibility that poor prognosis in EOC patients with T2DM is partly due to the accumulation of senescent T cells in the omentum. In this review, we explore this hypothesis with recent findings, potential therapeutic approaches, and future directions.

Elevated LINC00909 Promotes Tumor Progression of Ovarian Cancer via Regulating the miR-23b-3p/MRC2 Axis

Ovarian cancer (OC), the third common gynecologic malignancy, contributes to the most cancer-caused mortality in women. However, 70% of patients with OC are diagnosed at an advanced stage, of which the 5-year survival is less than 30%. Long noncoding RNAs (long ncRNAs or lncRNA), a type of RNA with exceeding 200 nucleotides in length but no protein-coding capability, have been demonstrated to involve the pathogenesis of various cancers and show considerable potential in the diagnosis of OC. In this study, we found that the LINC00909 expression in tumor and serum specimens of OC patients was elevated, determined by real-time quantitative, and droplet digital PCR. In receiver operating characteristic (ROC) analysis, our results revealed that serum LINC00909 distinguished cancers from normal ovarian tissue with 87.8% of sensitivity and 69.6% of specificity (AUC, 81.2%) and distinguished serous ovarian cancer from normal ovarian tissue with 90.0% of sensitivity and 75.9% of specificity (AUC, 84.5%). Furthermore, we observed that the tumor and serum LINC00909 level was positively associated with the International Federation of Gynecology and Obstetrics (FIGO) stage and the Eastern Cooperative Oncology Group (ECOG) score (reflecting patients' performance status). Also, patients with low serum LINC00909 level showed a longer overall (hazard ratio, HR = 1.874, p = 0.0004) and progression-free (HR = 1.656, p = 0.0017) survival. Functional assays indicated that the elevation of LINC00909 expression contributes to cell proliferation, migration, and invasion capability of ovarian cancer cells. Besides, we demonstrated that LINC00909 functions as a competing endogenous RNA (ceRNA) of MRC2 mRNA by sponging miR-23-3p, and thereby promotes epithelial-to-mesenchymal transition (EMT) of ovarian cancer cells. Therefore, we highlight that the LINC00909/miR-23b-3p/MRC2 axis is implicated in the pathogenesis of ovarian cancer, and serum LINC00909 may be a promising biomarker for the diagnosis of OC.

NOX4 Signaling Mediates Cancer Development and Therapeutic Resistance through HER3 in Ovarian Cancer Cells

Development of resistance to therapy in ovarian cancer is a major hinderance for therapeutic efficacy; however, new mechanisms of the resistance remain to be elucidated. NADPH oxidase 4 (NOX4) is responsible for higher NADPH activity to increase reactive oxygen species (ROS) production. In this study, we showed that higher levels of NOX4 were detected in a large portion of human ovarian cancer samples. To understand the molecular mechanism of the NOX4 upregulation, we showed that NOX4 expression was induced by HIF-1α and growth factor such as IGF-1. Furthermore, our results indicated that NOX4 played a pivotal role in chemotherapy and radiotherapy resistance in ovarian cancer cells. We also demonstrated that NOX4 knockdown increased sensitivity of targeted therapy and radiotherapy through decreased expression of HER3 (ERBB3) and NF-κB p65. Taken together, we identified a new HIF-1α/NOX4 signal pathway which induced drug and radiation resistance in ovarian cancer. The finding may provide a new option to overcome the therapeutic resistance of ovarian cancer in the future.

Radiomics and radiogenomics in ovarian cancer: a literature review

Ovarian cancer remains one of the most lethal gynecological cancers in the world despite extensive progress in the areas of chemotherapy and surgery. Many studies have postulated that this is because of the profound heterogeneity that underpins response to therapy and prognosis. Standard imaging evaluation using CT or MRI does not take into account this tumoral heterogeneity especially in advanced stages with peritoneal carcinomatosis. As such, newly emergent fields in the assessment of tumor heterogeneity have been proposed using radiomics to evaluate the whole tumor burden heterogeneity as opposed to single biopsy sampling. This review provides an overview of radiomics, radiogenomics, and proteomics and examines the use of these newly emergent fields in assessing tumor heterogeneity and its implications in ovarian cancer.

Predictive value of RAD51 on the survival and drug responsiveness of ovarian cancer

Background

Ovarian cancer has greatly endangered and deteriorated female health conditions worldwide. Refinement of predictive biomarkers could enable patient stratification and help optimize disease management.

Methods

RAD51 expression profile, target-disease associations, and fitness scores of RAD51 were analyzed in ovarian cancer using bioinformatic analysis. To further identify its role, gene enrichment analysis was performed, and a regulatory network was constructed. Survival analysis and drug sensitivity assay were performed to evaluate the effect of RAD51 expression on ovarian cancer prognosis. The predictive value of RAD51 was then confirmed in a validation cohort immunohistochemically.

Results

Ovarian cancer expressed more RAD51 than normal ovary. RAD51 conferred ovarian cancer dependency and was associated with ovarian cancer. RAD51 had extensive target-disease associations with various diseases, including ovarian cancer. Genes that correlate with and interact with RAD51 were involved in DNA damage repair and drug responsiveness. High RAD51 expression indicated unfavorable survival outcomes and resistance to platinum, taxane, and PARP inhibitors in ovarian cancer. In the validation cohort (126 patients), high RAD51 expression indicated platinum resistance, and platinum-resistant patients expressed more RAD51. Patients with high RAD51 expression had shorter OS (HR = 2.968, P < 0.0001) and poorer PFS (HR = 2.838, P < 0.0001). RAD51 expression level was negatively correlated with patients’ survival length.

Conclusions

Ovarian cancer had pronounced RAD51 expression and RAD51 conferred ovarian cancer dependency. High RAD51 expression indicated poor survival and decreased drug sensitivity. RAD51 has predictive value in ovarian cancer and can be exploited as a predictive biomarker.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-01953-5.

Computed Tomography Based Radiomics as a Predictor of Survival in Ovarian Cancer Patients: A Systematic Review

Simple Summary

Ovarian cancer represents the most lethal gynecological malignancy. Since many new drugs have been recently introduced as adjunctive treatments for this pathology, an early prediction of outcome might be helpful to further improve outcomes. Radiomics represents a recent advancement, relying on extraction of quantitative features from imaging examinations. Indeed, clinical images, such as computed tomography images, may contain quantitative information, reflecting the underlying pathophysiology of a tumoral tissue. Radiomic analyses can be performed in tumor regions and metastatic lesions, as well as in normal tissues. The radiomic process relies on quantitative features, usually extracted by dedicated software, and then culminates in analysis and model building, according to a defined clinical question. This systematic review aims to evaluate association between radiomics based on computed tomography images and survival (in terms of overall survival and progression free survival) in ovarian cancer patients.

Abstract

The objective of this systematic review was to assess the results of radiomics for prediction of overall survival (OS) and progression free survival (PFS) in ovarian cancer (OC) patients. A secondary objective was to evaluate the findings of papers that based their analyses on inter-site heterogeneity. This systematic review was conducted according to the PRISMA statement. After the initial retrieval of 145 articles, the final systematic review comprised six articles. Association between radiomic features and OS was evaluated in 3/6 studies (50%); all articles showed a significant association between radiomic features and OS. Association with PFS was evaluated in 5/6 (83%) articles; the period of follow-up ranged between six and 36 months. All the articles showed significant association between radiomic models and PFS. Inter-site textural features were used for analysis in 2/6 (33%) articles. They demonstrated that high levels of inter-site textural heterogeneity were significantly associated with incomplete surgical resection in breast cancer gene-negative patients, and that lower heterogeneity was associated with complete resectability. There were some differences among papers in methodology; for example, only 3/6 (50%) articles included validation cohorts. In conclusion, radiomic models have demonstrated promising results as predictors of survival in OC patients, although larger studies are needed to allow clinical applicability.

Diabetes mellitus and the risk of ovarian cancer: a systematic review and meta-analysis of cohort and case-control studies

OBJECTIVE

Emerging evidence from observational studies (cohort and case-control studies) suggests that a history of diabetes mellitus (DM) has been linked to increased risk of ovarian cancer (OC), but the association between them remains inconclusive. The aim of this systematic review and meta-analysis of observational studies was to clarify this association.

DESIGN

Systematic review and meta-analysis.

METHODS

We searched PubMed, Embase and the Cochrane library databases published from the inception through 9 April 2020 without language restriction. Observational studies that evaluated the correlation between DM and the incidence of OC were included in our study. Relative risk (RR) with 95% CI was pooled by use of a random-effects model.

RESULTS

A total of 36 epidemiological articles, including 9 case-control and 27 cohort studies, were finally enrolled, consisting of 14 496 incident cases of OC. Synthesised RRs of developing OC by history of DM were 1.20 (95% CI=1.10 to 1.31) for all eligible studies, 1.08 (95% CI=0.77 to 1.53) for case-control studies and 1.22 (95% CI=1.11 to 1.33) for cohort studies. The above-mentioned positive association persisted across most of subgroup analyses, whereas it was not significant among studies from North American and European countries, level of unadjusted, and patients with low-quality and gestational DM group. The cumulative meta-analysis and sensitivity analysis showed pooled effect was stable and reliable, and no apparent publication bias was identified in this study.

CONCLUSIONS

Our study found weaker but still association between DM and OC risk. However, further well-designed prospective studies that control for potential confounders are warranted.

HDAC6 Degradation Inhibits the Growth of High-Grade Serous Ovarian Cancer Cells

Simple Summary

The objective of this study was, firstly, to investigate the relationship between Histone deacetylase 6 (HDAC6) expression and survival in patients with ovarian cancer and, secondly, to test the effects of histone deacetylase 6 (HDAC6) inhibition on ovarian cancer cells in vitro. A meta-analysis of the correlation between HDAC6 gene expression and survival was performed on 3573 ovarian tumors from 19 datasets showed that high HDAC6 gene expression was associated with a decreased risk of death. Knockdown of HDAC6 gene expression with small interfering RNA (siRNA) and protein expression with a HDAC6 targeting protein degrader decreased ovarian cell proliferation, migration, and viability. Conversely, the selective inhibition of HDAC6 catalytic activity did not produce a robust inhibition of HDAC6 protein function. In summary, we demonstrated, for the first time, that HDAC6 over-expression in ovarian cancers is a favorable prognostic marker. We provide evidence to suggest that inhibition of HDAC6 catalytic activity has limited efficacy as a monotherapy in ovarian cancers.

Abstract

Histone deacetylase 6 (HDAC6) is a unique histone deacetylating enzyme that resides in the cell cytoplasm and is linked to the modulation of several key cancer related responses, including cell proliferation and migration. The promising anti-cancer response of the first-generation HDAC6 catalytic inhibitors continues to be assessed in clinical trials, although its role in high grade serous ovarian cancer is unclear. This study investigated HDAC6 tumor expression by immunohistochemistry in high-grade serous ovarian cancer (HGSOC) tissue samples and a meta-analysis of HDAC6 gene expression in ovarian cancer from publicly available data. The pharmacological activity of HDAC6 inhibition was assessed in a patient-derived model of HGSOC. HDAC6 was found to be highly expressed in HGSOC tissue samples and in the patient-derived HGSOC cell lines where higher HDAC6 protein and gene expression was associated with a decreased risk of death (hazard ratio (HR) 0.38, (95% confidence interval (CI), 0.16–0.88; p = 0.02); HR = 0.88 (95% CI, 0.78–0.99; p = 0.04)). Similarly, the multivariate analysis of HDAC6 protein expression, adjusting for stage, grade, and cytoreduction/cytoreductive surgery was associated with a decreased risk of death (HR = 0.19 (95% CI, 0.06–0.55); p = 0.002). Knock-down of HDAC6 gene expression with siRNA and protein expression with a HDAC6 targeting protein degrader decreased HGSOC cell proliferation, migration, and viability. Conversely, the selective inhibition of HDAC6 with the catalytic domain inhibitor, Ricolinostat (ACY-1215), inhibited HDAC6 deacetylation of α-tubulin, resulting in a sustained accumulation of acetylated α-tubulin up to 24 h in HGSOC cells, did not produce a robust inhibition of HDAC6 protein function. Inhibition of HGSOC cell proliferation by ACY-1215 was only achieved with significantly higher and non-selective doses of ACY-1215. In summary, we demonstrated, for the first time, that HDAC6 over-expression in HGSOC and all ovarian cancers is a favorable prognostic marker. We provide evidence to suggest that inhibition of HDAC6 catalytic activity with first generation HDAC6 inhibitors has limited efficacy as a monotherapy in HGSOC.

Chemotherapy sensitivity testing on ovarian cancer cells isolated from malignant ascites

BACKGROUND

In epithelial ovarian cancer (EOC), 15-20% of the tumors do not respond to first-line chemotherapy (paclitaxel with platinum-based therapy), and in recurrences this number increases. Our aim is to determine the feasibility of cell proliferation assays of tumor cells isolated from malignant ascites to predict in vitro chemotherapy sensitivity, and to correlate these results with clinical outcome.

MATERIALS AND METHODS

Ascites was collected from twenty women with advanced EOC. Cell samples were enriched for tumor cells and EOC origin was confirmed by intracellular staining of CK7, surface staining of CA125 and EpCAM, and HE4 gene expression. In vitro sensitivity to chemotherapy was determined in cell proliferation assays using intracellular ATP content as an indirect measure of cell number. In vitro drug response was quantified by calculation of the drug concentration at which cell growth was inhibited with 50%. Clinical outcome was determined using post-treatment CA125 level.

RESULTS

Cell samples of twenty patients were collected, of which three samples that failed to proliferate were excluded in the analysis (15%). Three other samples were excluded, because clinical outcome could not be determined correctly. In twelve of the fourteen remaining cases (86%) in vitro drug sensitivity and clinical outcome corresponded, while in two samples (14%) there was no correspondence.

CONCLUSIONS

Our study demonstrates the feasibility of drug sensitivity tests using tumor cells isolated from ascites of advanced EOC patients. Larger observational studies are required to confirm the correlation between the in vitro sensitivity and clinical outcome.

Clinical significance of microRNA-125b and its contribution to ovarian carcinogenesis

The underlying mechanisms of recurrence and metastasis of epithelial ovarian cancer (EOC) are largely unknown. In the present study, we investigated the clinical significance of microRNA-125b (miR-125b) and its role in ovarian tumorigenesis and progression. Seventy patients of EOC and paired tissues were enrolled from 2015 to 2017. qRT-PCR was used to evaluate miR-125b expression in tumor tissues and EOC cell line. Gain-and-loss function of miR-125b was achieved to explore the changes in cell biological function. We found that miR-125b expression in EOC tissues, especially in the high-grade tissues (P < 0.001), was significantly lower compared to the matched adjacent noncancerous tissues and associated with pathological type, stage, and overall survival (P < 0.05). Upregulation of miR-125b promoted apoptosis and decreased cell survival rate and migration, and vice versa in vitro. Mechanistically, miR-125b negatively regulated S100A4, a metastasis-associated protein. MiR-125b overexpression significantly decreased tumor growth and inhibited lung metastasis in vivo. Our results supported that miR-125b contributes to the progression of EOC by targeting S100A4. It potentially acts as a potential biomarker and therapeutic target of EOC.

Upregulated CXCL14 is associated with poor survival outcomes and promotes ovarian cancer cells proliferation

Ovarian cancer is one of the common malignant tumours of female reproductive organs. Due to early diagnosis difficulties and lack of effective treatment in the late stage, ovarian cancer has the highest mortality rate in female reproductive system malignancies. Therefore, finding reliable early diagnosis indicators and new therapeutic targets for ovarian cancer is an urgent problem to be solved. Chemokine (C-X-C motif) ligand 14 (CXCL14) is a small cytokine belonging to the CXC chemokine family, which has been found to possess multi-effects in tumourigenesis and development. Here, we reported that CXCL14 was preferentially expressed in ovarian cancer. By analysing the TCGA database, we found that CXCL14 was highly expressed in advanced ovarian cancer patients and correlated with poor prognosis. In addition, the abnormal high CXCL14 levels were observed in serum and ovarian tissue of ovarian cancer patients by qRT-PCR and ELISA. In vitro and in vivo experiments both confirmed that overexpression of CXCL14 promoted the ovarian cancer cell proliferation. Moreover, transfection of CXCL14 increased the phosphorylation level of signal transducer and activator of transcription 3 (STAT3), and administration of STAT3 inhibitor III inhibited the tumour-promoting effects of CXCL14. Therefore, our study suggests that CXCL14 could be utilised as a novel adjunct biomarker for early diagnosis of ovarian cancer and provides new targets and ideas for the treatment of advanced ovarian cancer. SIGNIFICANCE PARAGRAPH: CXCL14 could be utilised as a novel adjunct biomarker for early diagnosis of ovarian cancer and provides new targets and ideas for the treatment of advanced ovarian cancer.