scholarly journals Deletions on Chromosome Y and Downregulation of the SRY Gene in Tumor Tissue Are Associated with Worse Survival of Glioblastoma Patients

Cancers ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 1619
Author(s):  
Małgorzata Łysiak ◽  
Anja Smits ◽  
Kenney Roy Roodakker ◽  
Elisabeth Sandberg ◽  
Anna Dimberg ◽  
...  
Keyword(s):  
Gene Expression ◽  
Overall Survival ◽  
Growth Factor ◽  
Growth Factor Receptor ◽  
Enrichment Analysis ◽  
Digital Pcr ◽  
Gene Set Enrichment Analysis ◽  
Wild Type ◽  
Chromosome Y ◽  
Rank Analysis

Background: Biological causes of sex disparity seen in the prevalence of cancer, including glioblastoma (GBM), remain poorly understood. One of the considered aspects is the involvement of the sex chromosomes, especially loss of chromosome Y (LOY). Methods: Tumors from 105 isocitrate dehydrogenase (IDH) wild type male GBM patients were tested with droplet digital PCR for copy number changes of ten genes on chromosome Y. Decreased gene expression, a proxy of gene loss, was then analyzed in 225 IDH wild type GBM derived from TCGA and overall survival in both cohorts was tested with Kaplan–Meier log-rank analysis and maximally selected rank statistics for cut-off determination. Results: LOY was associated with significantly shorter overall survival (7 vs. 14.6 months, p = 0.0016), and among investigated individual genes survival correlated most prominently with loss of the sex-determining region Y gene (SRY) (10.8 vs. 14.8 months, p = 0.0031). Gene set enrichment analysis revealed that epidermal growth factor receptor, platelet-derived growth factor receptor, and MYC proto-oncogene signaling pathways are associated with low SRY expression. Conclusion: Our data show that deletions and reduced gene expression of chromosome Y genes, especially SRY, are associated with reduced survival of male GBM patients and connected to major susceptibility pathways of gliomagenesis.

scholarly journals Establishment of an Autophagy-Related Clinical Prognosis Model for Predicting the Overall Survival of Osteosarcoma

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Jianyi Li ◽  
Xiaojie Tang ◽  
Yukun Du ◽  
Jun Dong ◽  
Zheng Zhao ◽  
...  
Keyword(s):  
Gene Expression ◽  
Overall Survival ◽  
Molecular Mechanisms ◽  
Cox Regression ◽  
Enrichment Analysis ◽  
Risk Groups ◽  
Gene Set Enrichment Analysis ◽  
Data Set ◽  
Primary Tumor Site ◽  
Clinical Prognosis

Purpose. Osteosarcoma is the most common primary and highly invasive bone tumor in children and adolescents. The purpose of this study is to construct a multi-gene expression feature related to autophagy, which can be used to predict the prognosis of patients with osteosarcoma. Materials and methods. The clinical and gene expression data of patients with osteosarcoma were obtained from the target database. Enrichment analysis of autophagy-related genes related to overall survival (OS-related ARGs) screened by univariate Cox regression was used to determine OS-related ARGs function and signal pathway. In addition, the selected OS-related ARGs were incorporated into multivariate Cox regression to construct prognostic signature for the overall survival (OS) of osteosarcoma. Use the dataset obtained from the GEO database to verify the signature. Besides, gene set enrichment analysis (GSEA) were applied to further elucidate the molecular mechanisms. Finally, the nomogram is established by combining the risk signature with the clinical characteristics. Results. Our study eventually included 85 patients. Survival analysis showed that patients with low riskScore had better OS. In addition, 16 genes were included in OS-related ARGs. We also generate a prognosis signature based on two OS-related ARGs. The signature can significantly divide patients into low-risk groups and high-risk groups, and has been verified in the data set of GEO. Subsequently, the riskScore, primary tumor site and metastasis status were identified as independent prognostic factors for OS and a nomogram were generated. The C-index of nomogram is 0.789 (95% CI: 0.703~0.875), ROC curve and calibration chart shows that nomogram has a good consistency between prediction and observation of patients. Conclusions. ARGs was related to the prognosis of osteosarcoma and can be used as a biomarker of prognosis in patients with osteosarcoma. Nomogram can be used to predict OS of patients and improve treatment strategies.

scholarly journals Construction of a CXC Chemokine-Based Prediction Model for the Prognosis of Colon Cancer

2020 ◽  
Vol 2020 ◽  
pp. 1-12 ◽  
Author(s):  
Kaisheng Liu ◽  
Minshan Lai ◽  
Shaoxiang Wang ◽  
Kai Zheng ◽  
Shouxia Xie ◽  
...  
Keyword(s):  
Gene Expression ◽  
Colon Cancer ◽  
Overall Survival ◽  
Prediction Model ◽  
Enrichment Analysis ◽  
Forecast Model ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Characteristic Analysis ◽  
Incidence And Mortality

Colon cancer is the third most common cancer, with a high incidence and mortality. Construction of a specific and sensitive prediction model for prognosis is urgently needed. In this study, profiles of patients with colon cancer with clinical and gene expression data were downloaded from Gene Expression Omnibus and The Cancer Genome Atlas (TCGA). CXC chemokines in patients with colon cancer were investigated by differential expression gene analysis, overall survival analysis, receiver operating characteristic analysis, gene set enrichment analysis (GSEA), and weighted gene coexpression network analysis. CXCL1, CXCL2, CXCL3, and CXCL11 were upregulated in patients with colon cancer and significantly correlated with prognosis. The area under curve (AUC) of the multigene forecast model of CXCL1, CXCL11, CXCL2, and CXCL3 was 0.705 in the GSE41258 dataset and 0.624 in TCGA. The prediction model was constructed using the risk score of the multigene model and three clinicopathological risk factors and exhibited 92.6% and 91.8% accuracy in predicting 3-year and 5-year overall survival of patients with colon cancer, respectively. In addition, by GSEA, expression of CXCL1, CXCL11, CXCL2, and CXCL3 was correlated with several signaling pathways, including NOD-like receptor, oxidative phosphorylation, mTORC1, interferon-gamma response, and IL6/JAK/STAT3 pathways. Patients with colon cancer will benefit from this prediction model for prognosis, and this will pave the way to improve the survival rate and optimize treatment for colon cancer.

scholarly journals Identification of Potential Crucial Genes in Atrial Fibrillation: A Bioinformatic Analysis

2020 ◽  
Author(s):  
Junguo Zhang ◽  
Xin Huang ◽  
Xiaojie Wang ◽  
Yanhui Gao ◽  
Li Liu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Atrial Fibrillation ◽  
Growth Factor ◽  
Microarray Data ◽  
Therapeutic Targets ◽  
Enrichment Analysis ◽  
Bioinformatic Analysis ◽  
Gene Set Enrichment Analysis ◽  
Functional Enrichment ◽  
Insulin Like Growth Factor

Abstract Background Atrial fibrillation (AF) is clearly heritable, affecting 2-3% of the population in Europe and the USA. However, a substantial proportion of heritability is still lacking. In the present study, we aim to identify potential crucial genes associated with AF through bioinformatic analyses of public datasets.Methods Microarray data sets of GSE115574, GSE31821, GSE79768, GSE41177 and GSE14975 from the Gene Expression Omnibus (GEO) database were enrolled. After merging all microarray data and adjusted batch effect, differentially expressed genes (DEGs) were identified. Functional enrichment analyses based on Gene Ontology (GO) resource, Kyoto Encyclopedia of Genes and Genomes (KEGG) resource, Gene Set Enrichment Analysis (GSEA), Reactome Pathway Database and Disease Ontology (DO) were carried out for DEGs. Protein-protein interaction (PPI) network was constructed using the STRING database. Combined with aforementioned significant bioinformatics information, potential crucial genes were subsequently selected. The potential crucial genes coupled with corresponding predicted microRNAs involved in AF were then assessed.Result We identified 27 of DEGs with gene expression fold change (FC) ≥ 1.5 and 5 with FC ≥ 2 of AF patients compared with sinus rhythm controls. The most significantly enriched pathway was regulation of insulin-like growth factor transport and uptake by insulin-like growth factor binding proteins. IGFBP2, C1orf105, FHL2, CHGB, ATP1B4, IGFBP3, SLC26A9, CXCR4 and HTR2B were considered the potential crucial genes. Sixteen corresponding predicted microRNAs, of which 5 targeting IGFBP3 and 8 FHL2, might be associated with AF. The comparative toxicogenomics database (CTD) database showed CXCR4, IGFBP2, IGFBP3 and FHL2 had higher scores with AF.Conclusions The 9 potential crucial genes, especially CXCR4, IGFBP2, IGFBP3 and FHL2, may be associated with risk of AF. MicroRNAs targeting IGFBP3 and FHL2 may be potential biomarkers or therapeutic targets for AF. Our study provided new insights of AF into genetics, molecular pathogenesis and new therapeutic targets.

scholarly journals Identification of Potential Crucial Genes in Atrial Fibrillation: A Bioinformatic Analysis

2020 ◽  
Author(s):  
Junguo Zhang ◽  
Xin Huang ◽  
Xiaojie Wang ◽  
Yanhui Gao ◽  
Li Liu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Atrial Fibrillation ◽  
Growth Factor ◽  
Microarray Data ◽  
Enrichment Analysis ◽  
Bioinformatic Analysis ◽  
Gene Expression Omnibus ◽  
Gene Set Enrichment Analysis ◽  
Functional Enrichment ◽  
Insulin Like Growth Factor

Abstract Background Atrial fibrillation (AF) is at least partially heritable, affecting 2-3% of the population in Europe and the USA. However, a substantial proportion of heritability is still lacking. In the present study, we aim to identify potential crucial genes associated with AF through bioinformatic analyses of public datasets. Methods Microarray data sets of GSE115574, GSE31821, GSE79768, GSE41177 and GSE14975 from the Gene Expression Omnibus (GEO) database were retrieved. After merging all microarray data and adjusting batch effect, differentially expressed genes (DEGs) were identified. Functional enrichment analyses based on Gene Ontology (GO) resource, Kyoto Encyclopedia of Genes and Genomes (KEGG) resource, Gene Set Enrichment Analysis (GSEA), Reactome Pathway Database and Disease Ontology (DO) were carried out. Protein-protein interaction (PPI) network was constructed using the STRING database. Combined with aforementioned significant bioinformatics information, potential crucial genes were subsequently selected. The comparative toxicogenomics database (CTD) was carried out to explore the interaction between potential crucial genes and AF. Result We identified 27 of DEGs with gene expression fold change (FC) ≥ 1.5 or ≤ 2/3 (|log2 FC| ≥ 0.58) and 5 with FC ≥ 2 or ≤ 0.5 (|log2 FC| ≥ 1) of AF patients compared with sinus rhythm controls. The most significantly enriched pathway was regulation of insulin-like growth factor transport and uptake by insulin-like growth factor binding proteins. IGFBP2, C1orf105, FHL2, CHGB, ATP1B4, IGFBP3, SLC26A9, CXCR4 and HTR2B were considered the potential crucial genes. CTD showed CXCR4, IGFBP2, IGFBP3 and FHL2 had higher scores with AF. Conclusions The 9 potential crucial genes, especially CXCR4, IGFBP2, IGFBP3 and FHL2 , may be associated with risk of AF. Our study provided new insights of AF into genetics, molecular pathogenesis and new therapeutic targets.

scholarly journals Exploratory pooled analysis evaluating the effect of sequence of biological therapies on overall survival in patients with RAS wild-type metastatic colorectal carcinoma

ESMO Open ◽  
2018 ◽  
Vol 3 (2) ◽  
pp. e000297 ◽  
Author(s):  
Marc Peeters ◽  
Frédéric Forget ◽  
Meinolf Karthaus ◽  
Manuel Valladares-Ayerbes ◽  
Alberto Zaniboni ◽  
...  
Keyword(s):  
Overall Survival ◽  
Growth Factor ◽  
Colorectal Carcinoma ◽  
Growth Factor Receptor ◽  
Second Line ◽  
Wild Type ◽  
Metastatic Colorectal Carcinoma ◽  
First Line ◽  
Optimal Sequence ◽  
Link Type

BackgroundThe aim of this study was to evaluate the optimal sequence of targeted therapies (epidermal growth factor receptor inhibitors (EGFRi) and vascular endothelial growth factor inhibitors (VEGFi)), combined with chemotherapy, in patients with RAS wild-type (WT) metastatic colorectal carcinoma (mCRC). Exploratory analyses of overall survival (OS) for patients treated with either first-line panitumumab (EGFRi) and second-line VEGFi therapy, or first-line bevacizumab (VEGFi) and second-line EGFRi, were conducted.MethodsPatients from PEAK (NCT00819780), PRIME (NCT00364013) and Study 181 (NCT00339183), with RAS WT or RAS WT/BRAF WT tumours, were included in the analyses. OS data were pooled for patients receiving first-line panitumumab (PEAK and PRIME) or first-line bevacizumab (PEAK and 181), followed by second-line VEGFi or EGFRi, respectively.ResultsOverall, 104 RAS WT patients were included (n=66 panitumumab→VEGFi, n=38 bevacizumab→EGFRi). At the time of final data analysis, 63.6% versus 92.1% of patients in the panitumumab→VEGFi versus bevacizumab→EGFRi arms had died; median OS was 36.8 versus 27.8 months, respectively (HR 0.65; 95% CI 0.42 to 1.03). The OS HR for patients with RAS WT/BRAF WT mCRC overall was 0.58 (95% CI 0.36 to 0.95) and was 0.56 (95% CI 0.30 to 1.04) in those with left-sided tumours.ConclusionAlthough numbers are small, these exploratory analyses suggest a trend towards improved OS for first-line panitumumab plus chemotherapy followed by second-line VEGFi, compared with first-line bevacizumab followed by second-line EGFRi in patients with RAS WT and RAS WT/BRAF WT mCRC. Large prospective randomised trials are needed to further evaluate the optimum sequence of EGFRi/VEGFi in mCRC.

scholarly journals Prognostic Value of BIRC5 in Lung Adenocarcinoma Lacking EGFR, KRAS, and ALK Mutations by Integrated Bioinformatics Analysis

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Yajuan Cao ◽  
Weikang Zhu ◽  
Wanqing Chen ◽  
Jianchun Wu ◽  
Guozhen Hou ◽  
...  
Keyword(s):  
Gene Expression ◽  
Overall Survival ◽  
Lung Adenocarcinoma ◽  
Prognostic Value ◽  
Expression Profiles ◽  
Prognostic Significance ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Hub Genes

Objective. This study was aimed at investigating the prognostic significance of Baculoviral IAP repeat containing 5 (BIRC5) in lung adenocarcinoma (LAD) lacking EGFR, KRAS, and ALK mutations (triple-negative (TN) adenocarcinomas). Methods. The gene expression profiles were obtained from Gene Expression Omnibus (GEO). The identification of the differentially expressed genes (DEGs) was performed by GeneSpring GX. Gene set enrichment analysis (GSEA) was used to execute gene ontology function and pathway enrichment analysis. The protein interaction network was constructed by Cytoscape. The hub genes were extracted by MCODE and cytoHubba plugin from the network. Then, using BIRC5 as a candidate, the prognostic value in LAD and TN adenocarcinomas was verified by the Kaplan-Meier plotter and The Cancer Genome Atlas (TCGA) database, respectively. Finally, the mechanism of BIRC5 was predicted by a coexpressed network and enrichment analysis. Results. A total of 38 upregulated genes and 121 downregulated genes were identified. 9 hub genes were extracted. Among them, the mRNA expression of 5 genes, namely, BIRC5, MCM4, CDC20, KIAA0101, and TRIP13, were significantly upregulated among TN adenocarcinomas (all P<0.05). Notably, only the overexpression of BIRC5 was associated with unfavorable overall survival (OS) in TN adenocarcinomas (log rank P=0.0037). TN adenocarcinoma patients in the BIRC5 high-expression group suffered from a significantly high risk of distant metastasis (P=0.046), advanced N stage (P=0.033), and tumor-bearing (P=0.031) and deceased status (P=0.003). The mechanism of BIRC5 and coexpressed genes may be linked closely with the cell cycle. Conclusion. Overexpressed in tumors, BIRC5 is associated with unfavorable overall survival in TN adenocarcinomas. BIRC5 is a potential predictor and therapeutic target in TN adenocarcinomas.

scholarly journals Identification of Potential Crucial Genes in Atrial Fibrillation: A Bioinformatic Analysis

2020 ◽  
Author(s):  
Junguo Zhang ◽  
Xin Huang ◽  
Xiaojie Wang ◽  
Yanhui Gao ◽  
Li Liu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Atrial Fibrillation ◽  
Growth Factor ◽  
Microarray Data ◽  
Enrichment Analysis ◽  
Bioinformatic Analysis ◽  
Gene Expression Omnibus ◽  
Gene Set Enrichment Analysis ◽  
Functional Enrichment ◽  
Insulin Like Growth Factor

Abstract Background Atrial fibrillation (AF) is at least partially heritable, affecting 2-3% of the population in Europe and the USA. However, a substantial proportion of heritability is still lacking. In the present study, we aim to identify potential crucial genes associated with AF through bioinformatic analyses of public datasets. Methods Microarray data sets of GSE115574, GSE31821, GSE79768, GSE41177 and GSE14975 from the Gene Expression Omnibus (GEO) database were retrieved. After merging all microarray data and adjusting batch effect, differentially expressed genes (DEGs) were identified. Functional enrichment analyses based on Gene Ontology (GO) resource, Kyoto Encyclopedia of Genes and Genomes (KEGG) resource, Gene Set Enrichment Analysis (GSEA), Reactome Pathway Database and Disease Ontology (DO) were carried out. Protein-protein interaction (PPI) network was constructed using the STRING database. Combined with aforementioned significant bioinformatics information, potential crucial genes were subsequently selected. The comparative toxicogenomics database (CTD) was carried out to explore the interaction between potential crucial genes and AF. Result We identified 27 of DEGs with gene expression fold change (FC) ≥ 1.5 and 5 with FC ≥ 2 of AF patients compared with sinus rhythm controls. The most significantly enriched pathway was regulation of insulin-like growth factor transport and uptake by insulin-like growth factor binding proteins. IGFBP2, C1orf105, FHL2, CHGB, ATP1B4, IGFBP3, SLC26A9, CXCR4 and HTR2B were considered the potential crucial genes. CTD showed CXCR4, IGFBP2, IGFBP3 and FHL2 had higher scores with AF. Conclusions The 9 potential crucial genes, especially CXCR4, IGFBP2, IGFBP3 and FHL2 , may be associated with risk of AF. Our study provided new insights of AF into genetics, molecular pathogenesis and new therapeutic targets.

scholarly journals Identification of Potential Crucial Genes in Atrial Fibrillation: A Bioinformatic Analysis

2020 ◽  
Author(s):  
Junguo Zhang ◽  
Xin Huang ◽  
Xiaojie Wang ◽  
Yanhui Gao ◽  
Li Liu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Atrial Fibrillation ◽  
Growth Factor ◽  
Microarray Data ◽  
Enrichment Analysis ◽  
Bioinformatic Analysis ◽  
Gene Expression Omnibus ◽  
Gene Set Enrichment Analysis ◽  
Functional Enrichment ◽  
Insulin Like Growth Factor

Abstract Background Atrial fibrillation (AF) is at least partially heritable, affecting 2-3% of the population in Europe and the USA. However, a substantial proportion of heritability is still lacking. In the present study, we aim to identify potential crucial genes associated with AF through bioinformatic analyses of public datasets.Methods Microarray data sets of GSE115574, GSE31821, GSE79768, GSE41177 and GSE14975 from the Gene Expression Omnibus (GEO) database were retrieved. After merging all microarray data and adjusting batch effect, differentially expressed genes (DEGs) were identified. Functional enrichment analyses based on Gene Ontology (GO) resource, Kyoto Encyclopedia of Genes and Genomes (KEGG) resource, Gene Set Enrichment Analysis (GSEA), Reactome Pathway Database and Disease Ontology (DO) were carried out. Protein-protein interaction (PPI) network was constructed using the STRING database. Combined with aforementioned significant bioinformatics information, potential crucial genes were subsequently selected. The comparative toxicogenomics database (CTD) was used to explore the interaction between potential crucial genes and AF.Result We identified 27 of DEGs with gene expression fold change (FC) ≥ 1.5 or ≤ 2/3 (|log2 FC| ≥ 0.58) and 5 with FC ≥ 2 or ≤ 0.5 (|log2 FC| ≥ 1) of AF patients compared with sinus rhythm controls. The most significantly enriched pathway was regulation of insulin-like growth factor transport and uptake by insulin-like growth factor binding proteins. IGFBP2, C1orf105, FHL2, CHGB, ATP1B4, IGFBP3, SLC26A9, CXCR4 and HTR2B were considered the potential crucial genes. CTD showed CXCR4, IGFBP2, IGFBP3 and FHL2 had higher scores with AF.Conclusions The 9 potential crucial genes, especially CXCR4, IGFBP2, IGFBP3 and FHL2, may be associated with risk of AF. Our study provided new insights of AF into genetics, molecular pathogenesis and new therapeutic targets.

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