Fatty Acid Metabolism-Related lncRNA Prognostic Signature for Serous Ovarian Carcinoma

Abstract

Background: To explore the role of fatty acid metabolism (FAM)-related lncRNAs in the prognosis and antitumor immunity of serous ovarian cancer (SOC). Materials & methods: A SOC FAM-related lncRNA risk model was developed and evaluated by a series of analyses. Additional immune-related analyses were performed to further assess the associations between immune state, tumor microenvironment and the prognostic risk model. Results: Five lncRNAs associated with the FAM genes were found and used to create a predictive risk model. The patients with a low-risk profile exhibited favorable prognostic outcomes. Conclusion: The established prognostic risk model exhibits better predictive capabilities for the prognosis of patients with SOC and offers novel potential therapy targets for SOC.

Keywords::

• immunotherapy
• lncRNAs
• model
• overall survival
• tumor microenvironment

Supplementary data

To view the supplementary data that accompany this paper please visit the journal website at: www.futuremedicine.com/doi/suppl/10.2217/epi-2023-0388

Author contributions

W Lu, X Hong and S Zhang conceived, designed and supervised the study. L Ye performed bioinformatic analyses and visualization. L Ye, Z Jiang, K Pan, M Zheng and G Guo wrote the original manuscript. L Ye and Z Jiang performed the experiments. W Lu and X Hong reviewed and revised the manuscript. J Lian, B Ju, X Liu and S Tang collected the data. All authors have read and agreed to the published version of the manuscript.

Financial disclosure

This research was funded by the National Natural Science Foundation of China (NSFC) (nos. T2250610233, 82173391, 82072856). The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

Competing interests disclosure

The authors have no competing interests or relevant affiliations with any organization or entity with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

Writing disclosure

We would like to thank Editage (www.editage.cn) for English language editing.

Data sharing statement

The risk model generated in this study is publicly available (https://leley.shinyapps.io/famlnc/)

Additional information

Funding

This research was funded by the National Natural Science Foundation of China (NSFC) (nos. T2250610233, 82173391, 82072856). The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.