ArticleInternational journal of ophthalmology2021
Identification and validation of tumor microenvironment-related lncRNA prognostic signature for uveal melanoma.
Article in International journal of ophthalmology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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9 citing papers in PubMed, 13 citations in OpenAlex.
- A symphony of signals: the intricate role of lncRNAs in dermatological disorders.Clinical and experimental medicine · 2025Review
- Construction of a prognostic risk model for uveal melanoma based on immune-related long noncoding RNA.Medicine · 2024Article
- Construction of oxidative phosphorylation-related prognostic risk score model in uveal melanoma.BMC ophthalmology · 2024Article
- Identification and validation of a costimulatory molecule-related signature to predict the prognosis for uveal melanoma patients.Scientific reports · 2024Article
- Genetics and RNA Regulation of Uveal Melanoma.Cancers · 2023Review
- A prognostic model based on tumor microenvironment-related lncRNAs predicts therapy response in pancreatic cancer.Functional & integrative genomics · 2023Article
- A novel endoplasmic reticulum stress-related lncRNA prognostic risk model for cutaneous melanoma.Journal of cancer research and clinical oncology · 2022Article
- A prognostic signature based on cuprotosis-related long non-coding RNAs predicts the prognosis and sensitivity to chemotherapy in patients with colorectal cancer.Frontiers in medicine · 2022Article
- Identification of Immune-Related lncRNAs for Predicting Prognosis and Immune Landscape Characteristics of Uveal Melanoma.Journal of oncology · 2022Article
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
aimTo investigate the role of tumor microenvironment (TME)-related long non-coding RNA (lncRNA) in uveal melanoma (UM), probable prognostic signature and potential small molecule drugs using bioinformatics analysis.
methodsUM expression profile data were downloaded from the Cancer Genome Atlas (TCGA) and bioinformatics methods were used to find prognostic lncRNAs related to UM immune cell infiltration. The gene expression profile data of 80 TCGA specimens were analyzed using the single sample Gene Set Enrichment Analysis (ssGSEA) method, and the immune cell infiltration of a single specimen was evaluated. Finally, the specimens were divided into high and low infiltration groups. The differential expression between the two groups was analyzed using the R package 'edgeR'. Univariate, multivariate and Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression analyses were performed to explore the prognostic value of TME-related lncRNAs. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional analyses were also performed. The Connectivity Map (CMap) data set was used to screen molecular drugs that may treat UM.
resultsA total of 2393 differentially expressed genes were identified and met the criteria for the low and high immune cell infiltration groups. Univariate Cox analysis of lncRNA genes with differential expression identified 186 genes associated with prognosis. Eight prognostic markers of TME-included lncRNA genes were established as potentially independent prognostic elements. Among 269 differentially expressed lncRNAs, 69 were up-regulated and 200 were down-regulated. Univariate Cox regression analysis of the risk indicators and clinical characteristics of the 8 lncRNA gene constructs showed that age, TNM stage, tumor base diameter, and low and high risk indices had significant prognostic value. We screened the potential small-molecule drugs for UM, including W-13, AH-6809 and Imatinib.
conclusionThe prognostic markers identified in this study are reliable biomarkers of UM. This study expands our current understanding of the role of TME-related lncRNAs in UM genesis, which may lay the foundations for future treatment of this disease.
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