ArticleJournal of ovarian research2023
Developing four cuproptosis-related lncRNAs signature to predict prognosis and immune activity in ovarian cancer.
Article in Journal of ovarian research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Advancing the frontiers of ovarian cancer therapy: a comprehensive synthesis of emerging cell death paradigms.Oncology reviews · 2026Review
- Stemness-driven clusters in ovarian cancer: immune characteristics and prognostic implications.Frontiers in oncology · 2025Article
- Big data analysis and machine learning of the role of cuproptosis-related long non-coding RNAs (CuLncs) in the prognosis and immune landscape of ovarian cancer.Frontiers in immunology · 2025Article
- Development of CSOARG: a single-cell and multi-omics-based machine learning model for ovarian cancer prognosis and drug response prediction.Frontiers in oncology · 2025Article
- Characterization of Cuproptosis-Related LncRNAs Prognostic Signature and Identification of LINC02285 as a Novel Biomarker for Ovarian Cancer.Journal of inflammation research · 2025Article
- Identification of a Potential PGK1 Inhibitor with the Suppression of Breast Cancer Cells Using Virtual Screening and Molecular Docking.Pharmaceuticals (Basel, Switzerland) · 2024Article
- lncRNAs as prognostic markers and therapeutic targets in cuproptosis-mediated cancer.Clinical and experimental medicine · 2024Review
- Article
- A disulfidptosis-related lncRNAs cluster to forecast the prognosis and immune landscapes of ovarian cancer.Frontiers in genetics · 2024Article
- Copper homeostasis and cuproptosis in gynecological cancers.Frontiers in cell and developmental biology · 2024Review
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4 authors.
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Abstract
backgroundThere has been a recent discovery of a new type of cell death produced by copper-iron ions, called Cuproptosis (copper death). The purpose of this study was to identify LncRNA signatures associated with Cuproptosis in ovarian cancer that could be used as prognostic indicators.
methodsRNA sequencing (RNA-seq) profiles with clinicopathological data from TCGA database were used to select prognostic CRLs and then constructed prognostic risk model using multivariate regression analysis and LASSO algorithms. An independent dataset from GEO database was used to validate the prognostic performance. Combined with clinical factors, we further constructed a prognostic nomogram. In addition, tumor immune microenvironment, somatic mutation and drug sensitivity were analyzed using ssGSEA, GSVA, ESTIMATE and CIBERSORT algorithms.
resultA total of 129 CRLs were selected whose expression levels were significantly related to expression levels of 10 cuproptosis-related genes. The univariate Cox regression analysis showed that 12 CRLs were associated with overall survival (OS). Using LASSO algorithms and multivariate regression analysis, we constructed a four-CRLs prognostic signature in the training dataset. Patients in the training dataset could be classified into high- or low-risk subgroups with significantly different OS (log-rank p < 0.001). The prognostic performance was confirmed in TCGA-OC cohort (log-rank p < 0.001) and an independent GEO cohort (log-rank p = 0.023). Multivariate cox regression analysis proved the four-CRLs signature was an independent prognostic factor for OC. Additionally, different risk subtypes showed significantly different levels of immune cells, signal pathways, and drug response.
conclusionWe established a prognostic signature based on cuproptosis-related lncRNAs for OC patients, which will be of great value in predicting the prognosis patients and may provide a new perspective for research and individualized treatment.
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