Plasma circRNA microarray profiling identifies novel circRNA biomarkers for the diagnosis of ovarian cancer

CT-based radiomics predicts CD38 expression and indirectly reflects clinical prognosis in epithelial ovarian cancer

Background

Cluster of differentiation 38 (CD38) has been found to be highly expressed in various solid tumours, and its expression level may be associated with patient prognosis and survival. This study aimed to evaluate the prognostic value of CD38 expression for patients with epithelial ovarian cancer (EOC) and construct two computed tomography (CT)-based radiomics models for predicting CD38 expression.

Methods

A total of 333 cases of EOC were enrolled from The Cancer Genome Atlas (TCGA) database for CD38-related bioinformatics and survival analysis. A total of 56 intersection cases from TCGA and The Cancer Imaging Archive (TCIA) databases were selected for radiomics feature extraction and model construction. Logistic regression (LR) and support vector machine (SVM) models were constructed and internally validated using 5-fold cross-validation to assess the performance of the models for CD38 expression levels.

Results

High CD38 expression was an independent protective factor (HR = 0.540) for overall survival (OS) in EOC patients. Five radiomics features based on CT images were selected to build models for the prediction of CD38 expression. In the training and internal validation sets, for the receiver operating characteristic (ROC) curve, the LR model reached an area under the curve (AUC) of 0.739 and 0.732, while the SVM model achieved AUC values of 0.741 and 0.700, respectively. For the precision-recall (PR) curve, the LR and SVM models demonstrated an AUC of 0.760 and 0.721. The calibration curves and decision curve analysis (DCA) provided evidence supporting the fitness and net benefit of the models.

Conclusions

High levels of CD38 expression can improve OS in EOC patients. CT-based radiomics models can be a new predictive tool for CD38 expression, offering possibilities for individualised survival assessment for patients with EOC.

Current advances in circular RNA detection and investigation methods: Are we running in circles?

Circular RNAs (circRNAs), characterized by their closed-loop structure, have emerged as significant transcriptomic regulators, with roles spanning from microRNA sponging to modulation of gene expression and potential peptide coding. The discovery and functional analysis of circRNAs have been propelled by advancements in both experimental and bioinformatics tools, yet the field grapples with challenges related to their detection, isoform diversity, and accurate quantification. This review navigates through the evolution of circRNA research methodologies, from early detection techniques to current state-of-the-art approaches that offer comprehensive insights into circRNA biology. We examine the limitations of existing methods, particularly the difficulty in differentiating circRNA isoforms and distinguishing circRNAs from their linear counterparts. A critical evaluation of various bioinformatics tools and novel experimental strategies is presented, emphasizing the need for integrated approaches to enhance our understanding and interpretation of circRNA functions. Our insights underscore the dynamic and rapidly advancing nature of circRNA research, highlighting the ongoing development of analytical frameworks designed to address the complexity of circRNAs and facilitate the assessment of their clinical utility. As such, this comprehensive overview aims to catalyze further advancements in circRNA study, fostering a deeper understanding of their roles in cellular processes and potential implications in disease. This article is categorized under: RNA Methods > RNA Nanotechnology RNA Methods > RNA Analyses in Cells RNA Methods > RNA Analyses In Vitro and In Silico.

CircRAD23B promotes proliferation and carboplatin resistance in ovarian cancer cell lines and organoids

BACKGROUND

Circular RNAs (circRNAs) are involved in the regulation of progression and drug resistance in ovarian cancer (OC). In the present study, we aimed to explore the role of circRAD23B, a newly identified circRNA, in the regulation of carboplatin-resistant OC.

METHODS

CircRAD23B expression levels were measured using qRT-PCR. The biological roles of circRAD23B were analysed using CCK-8, colony formation, EDU, flow cytometry, and cell viability assays. RNA pull-down and luciferase assays were used to investigate the interactions of circRAD23B with mRNAs and miRNAs.

RESULTS

CircRAD23B was significantly increased in carboplatin-resistant OC tissues. CircRAD23B promoted proliferation and reduced sensitivity to carboplatin in cell lines and patient-derived organoids (PDOs), consistent with in vivo findings. Mechanistically, circRAD23B acted as a molecular sponge, abrogating its inhibitory effect on Y-box binding protein 1 (YBX1) by adsorbing miR-1287-5p. Rescue experiments confirmed that the pro-proliferation and carboplatin resistance mediated by circRAD23B was partially reversed by the upregulation of miR-1287-5p.

CONCLUSIONS

Our results demonstrated, for the first time, the role of the circRAD23B/miR-1287-5p/YBX1 axis in OC progression and carboplatin resistance in cell lines, PDOs, and animal models, providing a basis for the development of targeted therapies for patients with OC.

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.

Upregulation of circRNA_0023685 promotes gastric cancer progression via a circRNA-miRNA-mRNA interaction network

Circular RNAs (circRNAs) have been extensively studied for their critical roles as noncoding RNAs (ncRNAs) in gastric cancer (GC). In this study, we focused on the expression, function and molecular mechanism of circRNA_0023685 in gastric cancer (GC) to provide new ways for the diagnosis and treatment of GC. Firstly, a novel differentially expressed circRNA, circRNA_0023685, was identified, and its differential expression in GC plasma, tissue, and cell lines was further verified by RT-qPCR. Next, circRNA_0023685 was verified to promote the proliferation, migration and apoptosis of GC cells in vitro. CircRNA_0023685 was also proved to enhance the growth of GC tumors in xenograft models. Finally, for excavating the mechanism to promote GC, downstream microRNAs (miRNAs) and mRNAs were screened by bioinformatics analyses. After intersecting the target genes and genes enriched in GO analysis, a circRNA competing endogenous RNAs (ceRNAs) network was built. A protein-protein interaction (PPI) network was then constructed to find the candidate gene, APP. Our study confirmed that the highly expressed circRNA_0023685 could promote GC, which provided a new clinical diagnostic biomarker and therapeutic target for GC.

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.

Assessing the clinical utility of multi-omics data for predicting serous ovarian cancer prognosis

Ovarian cancer (OC) is characterised by heterogeneity that complicates the prediction of patient survival and treatment outcomes. Here, we conducted analyses to predict the prognosis of patients from the Genomic Data Commons database and validated the predictions by fivefold cross-validation and by using an independent dataset in the International Cancer Genome Consortium database. We analysed the somatic DNA mutation, mRNA expression, DNA methylation, and microRNA expression data of 1203 samples from 599 serous ovarian cancer (SOC) patients. We found that principal component transformation (PCT) improved the predictive performance of the survival and therapeutic models. Deep learning algorithms also showed better predictive power than the decision tree (DT) and random forest (RF). Furthermore, we identified a series of molecular features and pathways that are associated with patient survival and treatment outcomes. Our study provides perspective on building reliable prognostic and therapeutic strategies and further illuminates the molecular mechanisms of SOC.Impact statementWhat is already known on this subject? Recent studies have focussed on predicting cancer outcomes based on omics data. But the limitation is the performance of single-platform genomic analyses or the small numbers of genomic analyses.What do the results of this study add? We analysed multi-omics data, found that principal component transformation (PCT) significantly improved the predictive performance of the survival and therapeutic models. Deep learning algorithms also showed better predictive power than did decision tree (DT) and random forest (RF). Furthermore, we identified a series of molecular features and pathways that are associated with patient survival and treatment outcomes.What are the implications of these findings for clinical practice and/or further research? Our study provides perspective on how to build reliable prognostic and therapeutic strategies and further illuminates the molecular mechanisms of SOC for future studies.

Mechanisms of circRNA/lncRNA-miRNA interactions and applications in disease and drug research

In recent years, breakthroughs in bioinformatics have been made with the discovery of many functionally significant non-coding RNAs (ncRNAs). The discovery of these ncRNAs has further demonstrated the multi-level characteristics of intracellular gene expression regulation, which plays an important role in assisting diagnosis, guiding clinical drug use and determining prognosis in the treatment process of various diseases. microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs) are the three major types of ncRNAs that interact with each other. Studies have shown that lncRNAs and circRNAs can sponge miRNAs, thereby influencing normal physiological processes and regulating mRNA expression and, thus, the physiological state of cells. This paper summarizes the mechanism of action and research progress of the three ncRNA and seven types of modalities. This summary is intended to provide new ideas for diagnosing and treating diseases and researching and developing new drugs.

Roles and mechanisms of CircRNAs in ovarian cancer

Ovarian cancer (OC) is one of the female malignancies with nearly 45% 5-year survival rate. Circular RNAs (circRNAs), a kind of single-stranded non-coding RNAs, are generated from the back-splicing of cellular housekeeping noncoding RNAs and precursor messenger RNAs. Recent studies revealed that circRNAs have different biological function, including sponging miRNAs, encoding micropeptides, regulating stability of cytoplasmic mRNAs, affecting transcription and splicing, via interacting with DNA, RNA and proteins. Due to their stability, circRNAs have the potential of acting as biomarkers and treatment targets. In this review, we briefly illustrate the biogenesis mechanism and biological function of circRNAs in OC, and make a perspective of circRNAs drug targeting immune responses and signaling pathways in OC. This article can provide a systematic view into the current situation and future of circRNAs in OC.

Circular RNAs in Epithelial Ovarian Cancer: From Biomarkers to Therapeutic Targets

Epithelial ovarian cancer (EOC) is the most lethal gynecological cancer, and more than 70% of patients are diagnosed at advanced stages. Despite the application of surgery and chemotherapy, the prognosis remains poor due to the high relapse rate. It is urgent to identify novel biomarkers and develop novel therapeutic strategies for EOC. Circular RNAs (circRNAs) are a class of noncoding RNAs generated from the "back-splicing" of precursor mRNA. CircRNAs exert their functions via several mechanisms, including acting as miRNA sponges, interacting with proteins, regulating transcription, and encoding functional proteins. Recent studies have identified many circRNAs that are dysregulated in EOC and may be used as diagnostic and prognostic markers. Increasing evidence has revealed that circRNAs play a critical role in ovarian cancer progression by regulating various cellular processes, including proliferation, apoptosis, metastasis, and chemosensitivity. The circRNA-based therapy may be a novel strategy that is worth exploring in the future. Here, we provide an overview of EOC and circRNA biogenesis and functions. We then discuss the dysregulations of circRNAs in EOC and the possibility of using them as diagnostic/prognostic markers. We also summarize the role of circRNAs in regulating ovarian cancer development and speculate their potential as therapeutic targets.

m6A-modified circRNAs: detections, mechanisms, and prospects in cancers

Circular RNAs (circRNAs) have become a research hotspot in recent years with their universality, diversity, stability, conservativeness, and spatiotemporal specificity. N⁶-methyladenosine (m⁶A), the most abundant modification in the eukaryotic cells, is engaged in the pathophysiological processes of various diseases. An increasing amount of evidence has suggested that m⁶A modification is common in circRNAs and is associated with their biological functions. This review summarizes the effects of m⁶A modification on circRNAs and their regulation mechanisms in cancers, providing some suggestions of m⁶A-modified circRNAs in cancer therapy.