Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, No. 36, Sanhao Street, Heping District, Shenyang, 110004, China.
J Ovarian Res. 2023 Aug 26;16(1):177. doi: 10.1186/s13048-023-01247-6.
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.
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.
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.
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.
卵巢癌（OC）是女性生殖系统中最恶性的肿瘤，预后最差。自噬和长链非编码 RNA（lncRNA）在肿瘤发生、发展和耐药中起关键作用。自噬相关 lncRNA 对 OC 预后和治疗反应的影响仍不清楚。
我们从癌症基因组图谱数据库中检索 OC 相关的 RNA 序列、拷贝数变异、体细胞突变和临床病理信息，从 Reactome 数据库中检索自噬相关基因集。采用 Pearson 相关分析区分自噬相关 lncRNA。使用 UniCox、LASSO 和向前逐步回归分析构建预后 lncRNA 特征。将风险评分高于或低于中位数的个体分为高风险组和低风险组。使用 Kaplan-Meier 估计器、受试者工作特征曲线、决策曲线分析和 Cox 回归分析对风险模型进行分析，并使用内部数据集进行验证。在临床样本和 OC 细胞系中验证 LINC00174。我们还回顾了 LINC00174 在癌症中的作用的报告。随后，构建了一个列线图模型。此外，使用癌症基因组药物敏感性数据库探讨风险模型与抗肿瘤药物敏感性的关系。进行基因集变异分析以评估两组之间潜在的生物学功能差异。最后，构建了 lncRNA 预后特征相关竞争性内源性 RNA（ceRNA）网络。
预后特征显示，高危组患者预后较差。列线图表现出较好的准确性和预测潜力。LINC00174 主要在癌症中作为致癌基因发挥作用，在 OC 中上调；其敲低抑制 OC 细胞的增殖和迁移，促进凋亡。高危患者对顺铂和奥拉帕利的敏感性低于低危患者。ceRNA 网络可能有助于探索 lncRNA 的潜在调控机制。
自噬相关 lncRNA 特征可用于估计生存和药物敏感性，ceRNA 网络可能为 OC 患者提供新的治疗靶点。
