Tian Lingxi, Xu Feng, Lu Yang, Deng Zaian, Gao Yan, Yang Jun
MOE Key Laboratory of Intelligent Biomanufacturing, School of Bioengineering, Dalian University of Technology, Dalian, 116024, China.
Department of thoracic surgery, Dalian Municipal Central Hospital, Central Hospital of Dalian University of Technology, Dalian, 116033, China.
Sci Rep. 2025 Jul 16;15(1):25809. doi: 10.1038/s41598-025-11641-3.
The biological functions of circular RNA (circRNAs) in cancers have garnered significant attention, particularly for their potential as biomarkers. However, the roles of circRNAs in ovarian cancer (OC) and their applicability for early detection of this malignancy remain underexplored. We performed RNA sequencing on ovarian cancer cell lines to identify circRNAs associated with OC. The functional mechanisms of the identified circRNAs were elucidated through bioinformatics analysis. The discriminating ability of biomarkers was assessed using receiver operating characteristic (ROC) analysis. RNA sequencing analysis revealed that 170 known circRNAs were correlated with ovarian cancer. Through the circRNA-miRNA-mRNA regulatory network, we identified 9 circRNAs that interact with 8 miRNAs, subsequently regulating the expression of 324 mRNAs. Functional enrichment analysis, protein-protein interaction (PPI) network analysis, and hub gene analysis indicated that these circRNAs and miRNAs may play a role in regulating MAPK, Wnt, and ErbB signaling pathways. We validated these circRNAs and miRNAs expression profiles in cell, tissue, and plasma samples, identifying four candidates-hsa_circ_0049101, hsa_circ_0007440, hsa_circ_0006935, and hsa-miR-338-3p-that expression level positively correlate with ovarian cancer development. These markers were then combined into a circRNA and miRNA detection (CMD) panel for ovarian cancer detection. The area under the curve (AUC) values obtained from ROC analysis demonstrated that these individual candidates, as well as the CMD panel, exhibited superior discriminatory ability for OC compared to traditional biomarkers such as CA125, HE4, and the ROMA index in our sample set, which included 28 healthy controls and 22 ovarian cancer patients. Notably, the CMD panel showed exceptional potential for distinguishing early-stage OC samples from healthy controls, achieving an AUC of 1. In this study, we elucidated the functional mechanisms of a set of circRNAs associated with OC through multi-omics analysis and demonstrated that the combination of circRNAs and miRNAs into a biomarker panel holds significant potential for early detection of ovarian cancer.
环状RNA(circRNAs)在癌症中的生物学功能已引起广泛关注,尤其是其作为生物标志物的潜力。然而,circRNAs在卵巢癌(OC)中的作用及其在该恶性肿瘤早期检测中的适用性仍未得到充分探索。我们对卵巢癌细胞系进行了RNA测序,以鉴定与OC相关的circRNAs。通过生物信息学分析阐明了所鉴定circRNAs的功能机制。使用受试者工作特征(ROC)分析评估生物标志物的鉴别能力。RNA测序分析显示,170种已知的circRNAs与卵巢癌相关。通过circRNA-miRNA-mRNA调控网络,我们鉴定出9种与8种miRNA相互作用的circRNAs,随后调节324种mRNA的表达。功能富集分析、蛋白质-蛋白质相互作用(PPI)网络分析和枢纽基因分析表明,这些circRNAs和miRNAs可能在调节MAPK、Wnt和ErbB信号通路中发挥作用。我们在细胞、组织和血浆样本中验证了这些circRNAs和miRNAs的表达谱,确定了四个候选物——hsa_circ_0049101、hsa_circ_0007440、hsa_circ_0006935和hsa-miR-338-3p——其表达水平与卵巢癌发展呈正相关。然后将这些标志物组合成一个用于卵巢癌检测的circRNA和miRNA检测(CMD)面板。从ROC分析获得的曲线下面积(AUC)值表明,与我们样本集中的传统生物标志物如CA125、HE4和ROMA指数相比,这些单个候选物以及CMD面板对OC表现出更好的鉴别能力,我们的样本集包括28名健康对照和22名卵巢癌患者。值得注意的是,CMD面板在区分早期OC样本与健康对照方面显示出非凡的潜力,AUC达到1。在本研究中,我们通过多组学分析阐明了一组与OC相关的circRNAs的功能机制,并证明将circRNAs和miRNAs组合成生物标志物面板在卵巢癌早期检测中具有巨大潜力。