Dataset Information

Validation of an Ultraviolet Light Response Gene Signature for Predicting Prognosis in Patients with Uveal Melanoma.

ABSTRACT: Uveal melanoma (UVM) is a highly aggressive ocular cancer with limited therapeutic options and poor prognosis particularly for patients with liver metastasis. As such, the identification of new prognostic biomarkers is critical for developing effective treatment strategies. In this study, we aimed to investigate the potential of an ultraviolet light response gene signature to predict the prognosis of UVM patients. Our approach involved the development of a prognostic model based on genes associated with the cellular response to UV light. By employing this model, we generated risk scores to stratify patients into high- and low-risk groups. Furthermore, we conducted differential expression analysis between these two groups and explored the estimation of immune infiltration. To validate our findings, we applied our methodology to an independent UVM cohort. Through our study, we introduced a novel survival prediction tool and shed light on the underlying cellular processes within UVM tumors, emphasizing the involvement of immune subsets in tumor progression.

SUBMITTER: Orozco CA

PROVIDER: S-EPMC10377706 | biostudies-literature | 2023 Jul

REPOSITORIES: biostudies-literature

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Validation of an Ultraviolet Light Response Gene Signature for Predicting Prognosis in Patients with Uveal Melanoma.

Orozco Carlos A CA Mejía-García Alejandro A Ramírez Marcela M González Johanna J Castro-Vega Luis L Kreider Richard B RB Serrano Silvia S Combita Alba Lucia AL Bonilla Diego A DA

Biomolecules 20230719 7

Uveal melanoma (UVM) is a highly aggressive ocular cancer with limited therapeutic options and poor prognosis particularly for patients with liver metastasis. As such, the identification of new prognostic biomarkers is critical for developing effective treatment strategies. In this study, we aimed to investigate the potential of an ultraviolet light response gene signature to predict the prognosis of UVM patients. Our approach involved the development of a prognostic model based on genes associa ...[more]

PMID: 37509183

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Project description:IntroductionUveal melanoma (UM) is the most common primary intraocular malignant tumor in adults, and the main treatment for UM is currently surgery and plaque brachytherapy. UM is highly susceptible to metastasis, which eventually occurs in nearly half of all patients; once metastasis occurs, patients have a poor prognosis and the condition is difficult to treat. Therefore, the identification of new and effective UM biomarkers is vital for the application of therapeutic strategies. Immunogenic cell death (ICD) is a type of regulatory cell death that activates adaptive immune responses and generates long-term immunological memory. ICD can promote antitumor immunity, which may be a potential immunotherapeutic strategy for UM.MethodsThe data of UM from the Cancer Genome Atlas (TCGA) was used as a training set and the data from Gene Expression Omnibus (GEO) was used as a validation set. To determine the expression pattern of ICD-related genes in UM, survival analysis and difference analysis was conducted. The ICD-related risk signature was constructed by employing the least absolute shrinkage and selection operator (LASSO) Cox regression. Subsequently, immune profile and somatic mutation analysis were performed. In addition, cell experiments were performed to verify the role of immunogenic cell death-related genes in UM.ResultsIn this study, we analyzed the relationship between ICD-related gene expression and UM patient prognosis, somatic mutations, and the tumor immune microenvironment. Importantly, we constructed a 5-gene ICD-related risk signature and confirmed it as a novel prognostic biomarker in UM patients. We found that the high-risk group had more immune cell infiltration and a worse prognosis than the low-risk group. In cellular experiments, we confirmed the high expression of FOXP3 inMUM2B andOCM-1A cell lines and that knockdown of FOXP3 markedly inhibited the proliferation of UM tumor cells.DiscussionICD-related genes play a critical role in the tumor immune microenvironment. Our results may contribute to the development of effective immunotherapies.

Project description:BackgroundFerroptosis is a newly iron-dependent mode of programmed cell death that is involved in a variety of malignancies. But no research has shown a link between ferroptosis-related long non-coding RNAs (FRLs) and uveal melanoma (UM). We aimed to develop a predictive model for UM and explore its potential function in relation to immune cell infiltration.MethodsIdentification of FRLs was performed using the Cancer Genome Atlas (TCGA) and FerrDb databases. To develop a prognostic FRLs signature, univariate Cox regression and least absolute shrinkage and selection operator (LASSO) were used in training cohort. Kaplan-Meier (K-M) and receiver operating characteristic (ROC) curve analyses were used to assess the reliability of the risk model. The immunological functions of FRLs signature were determined using gene set enrichment analysis (GSEA). Immunological cell infiltration and immune treatment were studied using the ESTIMATE, CIBERSORT, and ssGSEA algorithms. Finally, in vitro assays were carried out to confirm the biological roles of FRLs with known primer sequences (LINC00963, PPP1R14B.AS1, and ZNF667.AS1).ResultsA five-genes novel FRLs signature was identified. The mean risk score generated by this signature was used to create two risk groups. The high-risk score UM patients had a lower overall survival rate. The area under the curve (AUC) of ROC and K-M analysis further validated the strong prediction capacity of the prognostic signature. Immune cells such as memory CD8 T cells, M1 macrophages, monocytes, and B cells showed a substantial difference between the two groups. GSEA enrichment results showed that the FRLs signature was linked to certain immune pathways. Moreover, UM patients with high-risk scores were highly susceptible to several chemotherapy drugs, such as cisplatin, imatinib, bortezomib, and pazopanib. Finally, the experimental validation confirmed that knockdown of three identified lncRNA (LINC00963, PPP1R14B.AS1, and ZNF667.AS1) suppressed the invasive ability of tumor cells in vitro.ConclusionThe five-FRLs (AC104129.1, AC136475.3, LINC00963, PPP1R14B.AS1, and ZNF667.AS1) signature has effects on clinical survival prediction and selection of immunotherapies for UM patients.

Project description:Uveal melanoma (UM) is the most common intraocular tumor in adults. Ferroptosis is a newly recognized process of cell death, which is different from other forms of cell death in terms of morphology, biochemistry and genetics, and has played a vital role in cancer biology. The present research aimed to construct a gene signature from ferroptosis-related genes that have the prognostic capacity of UM. UM patients from The Cancer Genome Atlas (TCGA) were taken as the training cohort, and GSE22138 from Gene Expression Omnibus (GEO) was treated as the validation cohort. A total of 103 ferroptosis-related genes were retrieved from the GeneCards. We performed Kaplan-Meier and univariate Cox analysis for preliminary screening of ferroptosis-related genes with potential prognostic capacity in the training cohort. These genes were then applied into an overall survival-based LASSO Cox regression model, constructing a gene signature. The discovered gene signature was then evaluated via Kaplan-Meier (KM), Cox, and ROC analyses in both cohorts. The Pearson correlation coefficient examined the correlations between risk score and UM common mutations and autophagy. The analyses of GSEA and immune infiltrating were performed to better study the functional annotation of the gene signature and the character of each kind of immune cell in the tumor microenvironment. A seven-gene signature was found from the training cohort and validated in all cohorts by Kaplan-Meier and Cox regression analyses, revealing its independent prognosis value in UM. Moreover, ROC analysis was conducted, confirming the strong predictive ability that this signature had for UM prognosis. A total of 52.24% (256/490) autophagy-related genes were significantly correlated with risk scores. Analyses of GSEA and immune infiltrating detailed exhibited specific pathways associated with the seven-gene signature, also confirming the crucial role that Mast cells resting played in the prognosis of the seven-gene signature. In this study, a novel ferroptosis-related seven-gene signature (ALOX12, CD44, MAP1LC3C, STEAP3, HMOX1, ITGA6, and AIFM2/FSP1) was built. It could accurately predict UM prognosis and was related to Mast cells resting, which provides the potential for personalized outcome prediction and the development of new therapies in the UM population.

Project description:BackgroundCD8+ T cells work as a key effector of adaptive immunity and are closely associated with immune response for killing tumor cells. It is crucial to understand the role of tumor-infiltrating CD8+ T cells in uveal melanoma (UM) to predict the prognosis and response to immunotherapy.Materials and methodsSingle-cell transcriptomes of UM with immune-related genes were combined to screen the CD8+ T-cell-associated immune-related genes (CDIRGs) for subsequent analysis. Next, a prognostic gene signature referred to tumor-infiltrating CD8+ T cells was constructed and validated in several UM bulk RNA sequencing datasets. The risk score of UM patients was calculated and classified into high- or low-risk subgroup. The prognostic value of risk score was estimated by using multivariate Cox analysis and Kaplan-Meier survival analysis. Moreover, the potential ability of gene signature for predicting immunotherapy response was further explored.ResultsIn total, 202 CDIRGs were screened out from the single-cell RNA sequencing of GSE139829. Next, a gene signature containing three CDIRGs (IFNGR1, ANXA6, and TANK) was identified, which was considered as an independent prognostic indicator to robustly predict overall survival (OS) and metastasis-free survival (MFS) of UM. In addition, the UM patients were classified into high- and low-risk subgroups with different clinical characteristics, distinct CD8+ T-cell immune infiltration, and immunotherapy response. Gene set enrichment analysis (GSEA) showed that immune pathways such as allograft rejection, inflammatory response, interferon alpha and gamma response, and antigen processing and presentation were all positively activated in low-risk phenotype.ConclusionOur work gives an inspiration to explain the limited response for the current immune checkpoint inhibitors to UM. Besides, we constructed a novel gene signature to predict prognosis and immunotherapy responses, which may be regarded as a promising therapeutic target.

Dataset Information

Validation of an Ultraviolet Light Response Gene Signature for Predicting Prognosis in Patients with Uveal Melanoma.

Publications

Validation of an Ultraviolet Light Response Gene Signature for Predicting Prognosis in Patients with Uveal Melanoma.

Similar Datasets

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