scholarly journals Screening and identification of potential prognostic biomarkers in metastatic skin cutaneous melanoma by bioinformatics analysis

2020 ◽  
Vol 24 (19) ◽  
pp. 11613-11618 ◽  
Author(s):  
Zufeng Sheng ◽  
Wei Han ◽  
Biao Huang ◽  
Guoliang Shen
Keyword(s):  
Cutaneous Melanoma ◽  
Bioinformatics Analysis ◽  
Prognostic Biomarkers ◽  
Screening And Identification

scholarly journals Identification of Biomarkers Related To The Diagnosis And Prognosis of Thyroid Cancer Through Bioinformatics Analysis

2021 ◽  
Author(s):  
Xiao-Li Xie ◽  
Hua-Li Yin ◽  
Yu-Lin Pan ◽  
Guo-Xia Li ◽  
Chun-Yan Yuan ◽  
...  
Keyword(s):  
Gene Expression ◽  
Thyroid Cancer ◽  
Bioinformatics Analysis ◽  
Prognostic Biomarkers ◽  
Cancer Tissue ◽  
Data Sets ◽  
Hub Genes ◽  
Normal Thyroid ◽  
Key Genes ◽  
Cancer Tissues

Abstract Background: Thyroid cancer is the most common malignant tumor of the head and neck. In recent years, the incidence of thyroid cancer (THCA) worldwide has rapidly increased and shows a trend in the younger generation. This study attempted to screen key genes and potential prognostic biomarkers for thyroid cancer using bioinformatics analysis.Methods: This study attempted to screen key genes and potential prognostic biomarkers for thyroid cancer using bioinformatics analysis. 101 cases of thyroid cancer and 78 cases of normal thyroid tissue were collected from three Gene Expression Omnibus (GEO) databases, then we identified the differentially expressed genes (DEGs) and conducted downstream analyses. Moreover, we screened hub genes by constructing a protein‐protein interaction (PPI) network. Finally, we assessed the expression level of hub genes in thyroid cancer tissue and its normal tissue using GEPIA and qRT-PCR respectively. Results: 159 upregulated and 251 downregulated genes were determined after gene integration of these three GEO data sets. Through PPI analysis, we consider the top 20 DEGs with high connectivity as the hub genes of THCA. After that, this study verified 20 central genes through the GEPIA database and found that only four hub genes (TOP2A, FN1, TIMP1, and MMP9) had significantly higher expression levels in thyroid cancer tissues than in normal thyroid tissues. We further analyzed the correlation between these four hub genes and the prognosis of patients with thyroid cancer, which suggests that FN1, MMP9, TIMP1 help assess the prognosis of patients with thyroid cancer. We performed GSEA analysis on these 4 hub genes simultaneously, found that the high expression of these 4 hub genes enriched the "cell cycle." Subsequently, we collected thyroid cancer tissue specimens, verified these four hub gene expression levels by RT-PCR, and found that only FN1 and TIMP1 genes in thyroid cancer tissues had significantly higher mRNA levels than normal tissues. Conclusions: Our research has identified 20 hub genes that may be related to the occurrence and development of thyroid cancer through multiple gene expression profile data sets and a series of comprehensive bioinformatics analyses. Further database and tissue validation analysis revealed that only 2 hub genes may be considered as potential prognostic biomarkers, including FN1 and TIMP1. In addition, these two hub genes are involved in the cell cycle, suggesting that they may play a role in the occurrence and development of thyroid cancer.

scholarly journals Unraveling the Relevance of ARL GTPases in Cutaneous Melanoma Prognosis through Integrated Bioinformatics Analysis

2021 ◽  
Vol 22 (17) ◽  
pp. 9260
Author(s):  
Cheila Brito ◽  
Bruno Costa-Silva ◽  
Duarte C. Barral ◽  
Marta Pojo
Keyword(s):  
T Cells ◽  
Membrane Trafficking ◽  
Cutaneous Melanoma ◽  
Cell Activation ◽  
Bioinformatics Analysis ◽  
Immune Cell ◽  
Adenosine Diphosphate ◽  
Copy Number Variations ◽  
Immune Microenvironment ◽  
Melanoma Prognosis

Cutaneous melanoma (CM) is the deadliest skin cancer, whose molecular pathways underlying its malignancy remain unclear. Therefore, new information to guide evidence-based clinical decisions is required. Adenosine diphosphate (ADP)-ribosylation factor-like (ARL) proteins are membrane trafficking regulators whose biological relevance in CM is undetermined. Here, we investigated ARL expression and its impact on CM prognosis and immune microenvironment through integrated bioinformatics analysis. Our study found that all 22 ARLs are differentially expressed in CM. Specifically, ARL1 and ARL11 are upregulated and ARL15 is downregulated regardless of mutational frequency or copy number variations. According to TCGA data, ARL1 and ARL15 represent independent prognostic factors in CM as well as ARL11 based on GEPIA and OncoLnc. To investigate the mechanisms by which ARL1 and ARL11 increase patient survival while ARL15 reduces it, we evaluated their correlation with the immune microenvironment. CD4+ T cells and neutrophil infiltrates are significantly increased by ARL1 expression. Furthermore, ARL11 expression was correlated with 17 out of 21 immune infiltrates, including CD8+ T cells and M2 macrophages, described as having anti-tumoral activity. Likewise, ARL11 is interconnected with ZAP70, ADAM17, and P2RX7, which are implicated in immune cell activation. Collectively, this study provides the first evidence that ARL1, ARL11, and ARL15 may influence CM progression, prognosis, and immune microenvironment remodeling.

scholarly journals Sex Difference of Ribosome in Stroke-Induced Peripheral Immunosuppression by Integrated Bioinformatics Analysis

2020 ◽  
Vol 2020 ◽  
pp. 1-15 ◽  
Author(s):  
Jian-Qin Xie ◽  
Ya-Peng Lu ◽  
Hong-Li Sun ◽  
Li-Na Gao ◽  
Pei-Pei Song ◽  
...  
Keyword(s):  
Gene Expression ◽  
Sex Difference ◽  
Bioinformatics Analysis ◽  
Prognostic Biomarkers ◽  
Pathway Enrichment Analysis ◽  
Loss Of Function ◽  
Ppi Network ◽  
Translational Initiation ◽  
Nonalcoholic Fatty Liver ◽  
Female Specific

Ischemic stroke (IS) greatly threatens human health resulting in high mortality and substantial loss of function. Recent studies have shown that the outcome of IS has sex specific, but its mechanism is still unclear. This study is aimed at identifying the sexually dimorphic to peripheral immune response in IS progression, predicting potential prognostic biomarkers that can lead to sex-specific outcome, and revealing potential treatment targets. Gene expression dataset GSE37587, including 68 peripheral whole blood samples which were collected within 24 hours from known onset of symptom and again at 24-48 hours after onset (20 women and 14 men), was downloaded from the Gene Expression Omnibus (GEO) datasets. First, using Bioconductor R package, two kinds of differentially expressed genes (DEGs) (nonsex-specific- and sex-specific-DEGs) were screened by follow-up (24-48 hours) vs. baseline (24 hours). 30 nonsex-specific DEGs (1 upregulated and 29 downregulated), 79 female-specific DEGs (25 upregulated and 54 downregulated), and none of male-specific DEGs were obtained finally. Second, bioinformatics analysis of female-specific DEGs was performed. Gene Ontology (GO) functional annotation analysis shows that DEGs were mainly enriched in translational initiation, cytosolic ribosome, and structural constituent of ribosome. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis shows that the top 6 enrichment pathways are ribosome, nuclear factor-­kappa B (NF-kappa B) signaling pathway, apoptosis, mineral absorption, nonalcoholic fatty liver disease, and pertussis. Three functional modules were clustered in the protein–protein interaction (PPI) network of DEGs. The top 10 key genes of the PPI network constructed were selected, including RPS14, RPS15A, RPS24, FAU, RPL27, RPL31, RPL34, RPL35A, RSL24D1, and EEF1B2. Sex difference of ribosome in stroke-induced peripheral immunosuppression may be the potential mechanism of sex disparities in outcome after IS, and women are more likely to have stroke-induced immunosuppression. RPS14, RPS15A, RPS24, FAU, RPL27, RPL31, RPL34, RPL35A, RSL24D1, and EEF1B2 may be novel prognostic biomarkers and potential therapeutic targets for IS.

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