研究目的：

本研究旨在基于正常卵巢组织、良性卵巢肿瘤组织及高级别浆液性卵巢癌组织来源的细胞外小囊泡（Tumor-derived small extracellular vesicles，Ti-sEVs）转录组数据，筛选具有潜在诊断价值的分子标志物。此外，通过对Ti-sEVs中差异表达的长链非编码RNA（long non-coding RNA，lncRNA）及信使RNA（Messenger RNA，mRNA）进行功能富集分析，探讨卵巢癌的潜在发病机制。通过体外实验验证关键差异lncRNA的表达水平，并评估其在卵巢癌患者中的诊断价值。同时结合脂质代谢组学分析卵巢癌的脂质代谢特征，并通过对差异脂质代谢物的通路富集分析，深入解析卵巢癌的病理生物学机制。

研究方法：

本研究共收集高级别浆液性卵巢癌组织（M组）5例、良性卵巢肿瘤组织（B组）5例及正常卵巢组织（N组）5例，分离提取Ti-sEVs，并筛选差异表达的lncRNA及mRNA。

基于基因本体（Gene Ontology，GO）分析及京都基因与基因组百科全书（Kyoto Encyclopedia of Genes and Genomes，KEGG）通路富集分析，探讨相关基因的潜在生物学功能，并使用R包“xCell”进行免疫细胞浸润分析。

采用荧光定量聚合酶链式反应（Quantitative real-time polymerase chain reaction， qRT-PCR）验证候选lncRNA RMRP的表达水平，并结合癌症基因组图谱（The Cancer Genome Atlas，TCGA）及基因表达综合数据库（Gene Expression Omnibus，GEO）探讨其表达水平与卵巢癌患者临床预后的关系。

利用超高效液相色谱-串联质谱技术对样本中的脂质代谢物进行定性定量分析，并结合单变量统计分析（p值）及多变量统计分析（正交偏最小二乘判别分析）筛选差异脂质代谢物，并进行KEGG功能注释及通路富集分析。

研究结果：

M组Ti-sEVs携带的lncRNA及mRNA表达谱相较于B组和N组存在显著差异。功能富集分析表明，这些差异基因可能与免疫调控及代谢重编程密切相关。

在M组中显著上调的lncRNA线粒体RNA加工内切酶的RNA组分（RNA component of mitochondrial RNA processing endoribonuclease，RMRP）在卵巢癌细胞系中亦呈高表达状态。Kaplan-Meier生存分析显示，在TCGA数据库中，RMRP高表达组患者的无病生存期显著短于低表达组（p= 0.013）。GSE102073数据集分析显示，RMRP高表达组的无进展生存期显著短于低表达组（p = 0.004），但总生存期无统计学差异（p=0.1）。GSE140082数据集分析表明，RMRP高表达组的无进展生存期及总生存期均显著短于低表达组（p=0.012；p=0.024）。此外，RMRP的表达水平与中性粒细胞浸润呈显著正相关（r=0.695，p=0.008），提示其可能在卵巢癌微环境的免疫调控中发挥重要作用。

M组的多种脂质分子代谢物的富集显著低于B组和N组。差异脂质分子代谢物富集于多条与脂质代谢相关的KEGG通路（如甘油酯代谢、胆固醇代谢、脂肪细胞中脂解调控以及脂肪消化与吸收）。

研究结论：

本研究系统解析了正常卵巢组织、良性卵巢肿瘤组织及卵巢癌组织来源的Ti-sEVs转录组特征，并发现lncRNA RMRP在卵巢癌组织及细胞系中显著上调，其高表达与患者的不良预后密切相关，具有潜在的诊断及预后标志物价值。

此外，卵巢癌组织的脂质代谢物谱与正常及良性卵巢组织相比存在显著差异，提示肿瘤可能通过调控脂质代谢过程（如增强脂质分解及能量供应）以适应其快速增殖的需求。进一步研究差异脂质代谢物的生物学功能及其在肿瘤微环境中的作用，有望为卵巢癌的早期诊断及靶向治疗提供新的理论依据和潜在靶点。

Objectives：

This study aims to identify potential molecular biomarkers for ovarian cancer diagnosis based on transcriptomic data from tumor-derived small extracellular vesicles (Ti-sEVs) originating from normal ovarian tissue, benign ovarian tumor tissue, and high-grade serous ovarian cancer (HGSOC) tissue. Furthermore, by performing functional enrichment analysis of differentially expressed long non-coding RNAs (lncRNAs) and messenger RNAs (mRNAs) in Ti-sEVs, the study explores potential mechanisms underlying ovarian cancer pathogenesis. Key differentially expressed lncRNAs are further validated through in vitro experiments to assess their diagnostic value in ovarian cancer patients. Additionally, a lipidomic analysis is conducted to characterize lipid metabolism in ovarian cancer, and pathway enrichment analysis of differential lipid metabolites is performed to elucidate the pathobiological mechanisms of ovarian cancer.

Methods：                                                                                                               

Ti-sEVs were isolated and extracted from ovarian tissues of five HGSOC patients (M group), five benign ovarian tumor patients (B group), and five normal ovarian tissue samples (N group). Differentially expressed lncRNAs and mRNAs were identified.

Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were conducted to explore the biological functions of relevant genes, and immune cell infiltration analysis was performed using the R package "xCell."

The expression level of the candidate lncRNA RMRP was validated using quantitative real-time polymerase chain reaction (qRT-PCR). Additionally, its correlation with clinical prognosis in ovarian cancer patients was investigated using data from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO).

Lipid metabolites in the samples were qualitatively and quantitatively analyzed using ultra-high-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). Differential lipid metabolites were identified through univariate (p-value) and multivariate (orthogonal partial least squares discriminant analysis) statistical analyses. KEGG annotation and pathway enrichment analysis were performed to explore their biological significance.

Results：

The expression profiles of lncRNAs and mRNAs carried by Ti-sEVs in the M group exhibited significant differences compared to the B and N groups. Functional enrichment analysis suggested that these differentially expressed genes were closely associated with immune regulation and metabolic reprogramming.

The lncRNA RNA Component of Mitochondrial RNA Processing Endoribonuclease（RMRP）, which was significantly upregulated in the M group, also showed high expression levels in ovarian cancer cell lines. Kaplan-Meier survival analysis revealed that patients in the TCGA cohort with high RMRP expression had significantly shorter disease-free survival (p=0.013). Analysis of the GSE102073 dataset indicated that high RMRP expression was associated with a significantly shorter progression-free survival (p=0.004), though no significant difference was observed in overall survival (p=0.1). Analysis of the GSE140082 dataset demonstrated that both progression-free survival (PFS) and overall survival (OS) were significantly shorter in the high RMRP expression group (p=0.012; p=0.024). Moreover, RMRP expression was positively correlated with neutrophil infiltration (r=0.695, p=0.008), suggesting its potential role in immune regulation within the ovarian cancer microenvironment.

The enrichment of various lipid metabolites was significantly lower in the M group compared to the B and N groups. Differential lipid metabolites were predominantly enriched in KEGG pathways related to lipid metabolism, including glyceride metabolism, cholesterol metabolism, lipolysis regulation in adipocytes, and lipid digestion and absorption.

Conclusion：

This study systematically analyzed the transcriptomic characteristics of Ti-sEVs derived from normal ovarian tissue, benign ovarian tumors, and ovarian cancer tissue, identifying lncRNA RMRP as a significantly upregulated molecule in ovarian cancer tissues and cell lines. Its high expression was closely associated with poor prognosis, highlighting its potential as a diagnostic and prognostic biomarker.

Additionally, lipidomic analysis revealed significant differences in the lipid metabolite profile of ovarian cancer tissues compared to normal and benign ovarian tissues. These findings suggest that ovarian cancer may regulate lipid metabolism, such as enhancing lipid breakdown and energy supply, to support rapid tumor proliferation. Further investigation into the biological functions of differential lipid metabolites and their roles in the tumor microenvironment may provide novel insights for early ovarian cancer diagnosis and targeted therapeutic strategies.