Dataset Information

Screening and identification of key genes and pathways in metastatic uveal melanoma based on gene expression using bioinformatic analysis.

ABSTRACT: The current study aimed to elucidate the molecular mechanisms and identify the potential key genes and pathways for metastatic uveal melanoma (UM) using bioinformatics analysis.Gene expression microarray data from GSE39717 included 39 primary UM tissue samples and 2 metastatic UM tissue samples. Differentially expressed genes (DEGs) were generated using Gene Expression Omnibus 2R. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using the online Database for Annotation, Visualization and Integrated Discovery (DAVID) tool. The web-based STRING tool was adopted to construct a protein--protein interaction (PPI) network. The MCODE tool in Cytoscape was used to generate significant modules of the PPI network.A total of 213 DEGs were identified. GO and KEGG analyses revealed that the upregulated genes were mainly enriched in extracellular matrix organization and blood coagulation cascades, while the downregulated DEGs were mainly related to protein binding, negative regulation of ERK cascade, nucleus and chromatin modification, and lung and renal cell carcinoma. The most significant module was extracted from the PPI network. GO and KEGG enrichment analyses of the module revealed that the genes were mainly enriched in the extracellular region and space organization, blood coagulation process, and PI3K-Akt signaling pathway. Hub genes, including FN1, APOB, F2, SERPINC1, SERPINA1, APOA1, FGG, PROC, ITIH2, VCAN, TFPI, CXCL8, CDH2, and HP, were identified from DEGs. Survival analysis and hierarchical clustering results revealed that most of the hub genes were associated with prognosis and clinical progression.Results of this bioinformatics analysis may provide predictive biomarkers and potential candidate therapeutic targets for individuals with metastatic UM.

SUBMITTER: Xie J

PROVIDER: S-EPMC7581038 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Screening and identification of key genes and pathways in metastatic uveal melanoma based on gene expression using bioinformatic analysis.

Xie Jialu J Wu Zhenyu Z Xu Xiaogang X Liang Guanlu G Xu Jiehui J

Medicine 20201001 43

The current study aimed to elucidate the molecular mechanisms and identify the potential key genes and pathways for metastatic uveal melanoma (UM) using bioinformatics analysis.Gene expression microarray data from GSE39717 included 39 primary UM tissue samples and 2 metastatic UM tissue samples. Differentially expressed genes (DEGs) were generated using Gene Expression Omnibus 2R. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed usi ...[more]

PMID: 33120861

Similar Datasets

Project description:PurposeUveal melanoma is a rare melanoma variant with no effective therapies once metastases develop. Although durable cancer regression can be achieved in metastatic cutaneous melanoma with immunotherapies that augment naturally existing antitumor T-cell responses, the role of these treatments for metastatic uveal melanoma remains unclear. We sought to define the relative immunogenicity of these two melanoma variants and determine whether endogenous antitumor immune responses exist against uveal melanoma.Experimental designWe surgically procured liver metastases from uveal melanoma (n = 16) and cutaneous melanoma (n = 35) patients and compared the attributes of their respective tumor cell populations and their infiltrating T cells (TIL) using clinical radiology, histopathology, immune assays, and whole-exomic sequencing.ResultsDespite having common melanocytic lineage, uveal melanoma and cutaneous melanoma metastases differed in their melanin content, tumor differentiation antigen expression, and somatic mutational profile. Immunologic analysis of TIL cultures expanded from these divergent forms of melanoma revealed cutaneous melanoma TIL were predominantly composed of CD8(+) T cells, whereas uveal melanoma TIL were CD4(+) dominant. Reactivity against autologous tumor was significantly greater in cutaneous melanoma TIL compared with uveal melanoma TIL. However, we identified TIL from a subset of uveal melanoma patients which had robust antitumor reactivity comparable in magnitude with cutaneous melanoma TIL. Interestingly, the absence of melanin pigmentation in the parental tumor strongly correlated with the generation of highly reactive uveal melanoma TIL.ConclusionsThe discovery of this immunogenic group of uveal melanoma metastases should prompt clinical efforts to determine whether patients who harbor these unique tumors can benefit from immunotherapies that exploit endogenous antitumor T-cell populations. Clin Cancer Res; 22(9); 2237-49. ©2015 AACR.

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

Screening and identification of key genes and pathways in metastatic uveal melanoma based on gene expression using bioinformatic analysis.

Publications

Screening and identification of key genes and pathways in metastatic uveal melanoma based on gene expression using bioinformatic analysis.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets