Identification of Immune-Related lncRNAs for Predicting Prognosis and Immune Landscape Characteristics of Uveal Melanoma

Abstract

Immune-related genes and long noncoding RNAs (lncRNAs) have a significant impact on the prognostic value and immunotherapeutic response of uveal melanoma (UM). Therefore, we tried to develop a prognostic model on the basis of irlncRNAs for predicting prognosis and response on immunotherapy of UM patients. We identified 1,664 immune-related genes and 2,216 immune-related lncRNAs (irlncRNAs) and structured a prognostic model with 3 prognostic irlncRNAs by co-expression analysis, univariable Cox, LASSO, and multivariate Cox regression analyses. The Kaplan–Meier analysis indicated that patients in the high-risk group had a shorter survival time than patients in the low-risk group. The ROC curves demonstrated the high sensitivity and specificity of the signature for survival prediction, and the one-, three-, and five-year AUC values, respectively, were 0.974, 0.929, and 0.941 in the entire set. Cox regression analysis, C-index, DCA, PCA analysis, and nomogram were also applied to assess the validity and accuracy of the risk model. The GO and KEGG enrichment analyses indicated that this signature is significantly related to immune-related pathways and molecules. Finally, we investigated the immunological characteristics and immunotherapy of the model and identified various novel potential compounds in the model for UM. In summary, we constructed a new model on the basis of irlncRNAs that can accurately predict prognosis and response on immunotherapy of UM patients, which may provide valuable clinical applications in antitumor immunotherapy.

Multiple epigenetic modification profiles reveal the tumor immune microenvironment and clinical outcomes of uveal melanoma

“…As some Frontiers in Genetics frontiersin.org research showed, NSUN2-mediated RNA m5C alteration regulates the migration and proliferation of UM cells (Su et al, 2021). As Jiehua Deng et al identified, m7G may be able to control both CD8 + T cells and regulatory T cells (Treg cells), and they also suggest a connection between m7G and the prognosis of melanoma (Chen et al, 2022;Deng et al, 2022). Exploration of m7G-related lncRNA prognostic signature for predicting the immunological state in melanoma was demonstrated by Rong et al (2022).…”

“…As was already indicated, the signatures currently being utilized to explore the prognosis of UM patients are inadequate and not sufficiently Frontiers in Genetics frontiersin.org 09 rich. When clinical results and MRGs in UM and the tumor microenvironment were investigated, it was discovered that the TME is very important in UM (Chen et al, 2022). Researchers used MRGs to analyze immune response signatures and make prognostic predictions.…”

Genetics and RNA Regulation of Uveal Melanoma

“…Included in a prognostic signature; high levels associated with low survival rates [270] AC104117.3 Downregulated in high-risk tumors [271] AC104129.1…”

“…Included in a prognostic signature; high levels associated with low survival rates [269] Upregulated in high-risk tumors [271] BACE1-AS Low levels associated with low survival rates [276] BOLA3-AS1…”

“…A recent analysis of the TCGA dataset allowed to identify 1664 immune-related genes and 2216 lncRNAs thanks to expression correlation analysis. Through regression analysis, a signature of three lncRNAs (AP005121.1, AC104117.3, and SOX1-OT) able to predict OS was identified [271]. As previously discussed, Yu et al used TCGA expression data to identify a prognostic signature including five mRNAs (CGREF1, P4HA2, RGMB, PKNOX2, SLC6A6), four miRNAs (miR-181b, miR-507, miR-548, miR-181a) and six lncRNAs (PVT1, HCP5, EPB41L4A-AS1, BOLA3-AS1, SNHG7, GAS5).…”