4.6 Article

Mitophagy-related long non-coding RNA signature predicts prognosis and drug response in Ovarian Cancer

期刊

JOURNAL OF OVARIAN RESEARCH
卷 16, 期 1, 页码 -

出版社

BMC
DOI: 10.1186/s13048-023-01247-6

关键词

Mitophagy; Long non-coding RNAs; LINC00174; Competitive endogenous RNAs; Ovarian cancer; Prognosis; Drug sensitivity

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This study utilized The Cancer Genome Atlas and Reactome databases to retrieve ovarian cancer (OC)-related data and identify mitophagy-related long non-coding RNAs (lncRNAs). A prognostic lncRNA signature was constructed to estimate OC prognosis and therapeutic response. The signature showed that patients in the high-risk group had a poorer prognosis, and a ceRNA network was constructed to explore the potential regulatory mechanisms of lncRNAs.
Background 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.Methods 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.Results 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.Conclusion 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.

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