Dataset Information

Immune classification and identification of prognostic genes for uveal melanoma based on six immune cell signatures.

ABSTRACT: Cutaneous melanoma could be treated by immunotherapy, which only has limited efficacy on uveal melanoma (UM). UM immunotyping for predicting immunotherapeutic responses and guiding immunotherapy should be better understood. This study identified molecular subtypes and key genetic markers associated with immunotherapy through immunosignature analysis. We screened a 6-immune cell signature simultaneously correlated with UM prognosis. Three immune subtypes (IS) were determined based on the 6-immune cell signature. Overall survival (OS) of IS3 was the longest. Significant differences of linear discriminant analysis (LDA) score were detected among the three IS types. IS3 with the highest LDA score showed a low immunosuppression. IS1 with the lowest LDA score was more immunosuppressive. LDA score was significantly negatively correlated with most immune checkpoint-related genes, and could reflect UM patients' response to anti-PD1 immunotherapy. Weighted correlation network analysis (WGCNA) identified that salmon, purple, yellow modules were related to IS and screened 6 prognostic genes. Patients with high-expressed NME1 and TMEM255A developed poor prognosis, while those with high-expressed BEX5 and ROPN1 had better prognosis. There was no notable difference in OS between patients with high-expressed LRRN1 and ST13 and those with low-expressed LRRN1 and ST13. NME1, TMEM255A, Bex5 and ROPN1 showed potential prognostic significance in UM.

SUBMITTER: Gao G

PROVIDER: S-EPMC8593069 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Immune classification and identification of prognostic genes for uveal melanoma based on six immune cell signatures.

Gao Guohong G Yu Zhilong Z Zhao Xiaoyan X Fu Xinyi X Liu Shengsheng S Liang Shan S Deng Aijun A

Scientific reports 20211115 1

Cutaneous melanoma could be treated by immunotherapy, which only has limited efficacy on uveal melanoma (UM). UM immunotyping for predicting immunotherapeutic responses and guiding immunotherapy should be better understood. This study identified molecular subtypes and key genetic markers associated with immunotherapy through immunosignature analysis. We screened a 6-immune cell signature simultaneously correlated with UM prognosis. Three immune subtypes (IS) were determined based on the 6-immune ...[more]

PMID: 34782661

Similar Datasets

Project description:BackgroundUveal melanoma (UM) is the most common primary intraocular malignancy in adults. Many previous studies have demonstrated that the infiltrating of immune and stromal cells in the tumor microenvironment contributes significantly to prognosis.MethodsDataset TCGA-UVM, download from TCGA portal, was taken as the training cohort, and GSE22138, obtained from GEO database, was set as the validation cohort. ESTIMATE algorithm was applied to find intersection differentially expressed genes (DEGs) among tumor microenvironment. Kaplan-Meier analysis and univariate Cox regression model were performed on intersection DEGs to initial screen for potential prognostic genes. Then these genes entered into the validation cohort for validation using the same methods as that in the training cohort. Moreover, we conducted correlation analyses between the genes obtained in the validation cohort and the status of chromosome 3, chromosome 8q, and tumor metastasis to get prognosis genes. At last, the immune infiltration analysis was performed between the prognostic genes and 6 main kinds of tumor-infiltrating immune cells (TICs) for understanding the role of the genes in the tumor microenvironment.Results959 intersection DEGs were found in the UM microenvironment. Kaplan-Meier and Cox analysis was then performed in the training and validation cohorts on these DEGs, and 52 genes were identified with potential prognostic value. After comparing the 52 genes to chromosome 3, chromosome 8q, and metastasis, we obtained 21 genes as the prognostic genes. The immune infiltration analysis showed that Neutrophil had the potential prognostic ability, and almost every prognostic gene we had identified was correlated with abundances of Neutrophil and CD8+ T Cell.ConclusionsIdentifying 21 prognosis genes (SERPINB9, EDNRB, RAPGEF3, HFE, RNF43, ZNF415, IL12RB2, MTUS1, NEDD9, ZNF667, AZGP1, WARS, GEM, RAB31, CALHM2, CA12, MYEOV, CELF2, SLCO5A1, ISM1, and PAPSS2) could accurately identify patients' prognosis and had close interactions with Neutrophil in the tumor environment, which may provide UM patients with personalized prognosis prediction and new treatment insights.

Dataset Information

Immune classification and identification of prognostic genes for uveal melanoma based on six immune cell signatures.

Publications

Immune classification and identification of prognostic genes for uveal melanoma based on six immune cell signatures.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets