scholarly journals Identification of Potential Signatures and Their Functions for Acute Lymphoblastic Leukemia: A Study Based on the Cancer Genome Atlas

2021 ◽  
Vol 12 ◽  
Author(s):  
Weimin Wang ◽  
Chunhui Lyu ◽  
Fei Wang ◽  
Congcong Wang ◽  
Feifei Wu ◽  
...  
Keyword(s):  
Acute Lymphoblastic Leukemia ◽  
Real Time ◽  
Lymphoblastic Leukemia ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Hub Genes ◽  
Cerna Network ◽  
Cancer Genome Atlas ◽  
Genome Atlas ◽  
Real Time Qpcr

ObjectiveAcute lymphoblastic leukemia (ALL) is a malignant disease most commonly diagnosed in adolescents and young adults. This study aimed to explore potential signatures and their functions for ALL.MethodsDifferentially expressed mRNAs (DEmRNAs) and differentially expressed long non-coding RNAs (DElncRNAs) were identified for ALL from The Cancer Genome Atlas (TCGA) and normal control from Genotype-Tissue Expression (GTEx). DElncRNA–microRNA (miRNA) and miRNA–DEmRNA pairs were predicted using online databases. Then, a competing endogenous RNA (ceRNA) network was constructed. Functional enrichment analysis of DEmRNAs in the ceRNA network was performed. Protein–protein interaction (PPI) network was then constructed. Hub genes were identified. DElncRNAs in the ceRNA network were validated using Real-time qPCR.ResultsA total of 2,903 up- and 3,228 downregulated mRNAs and 469 up- and 286 downregulated lncRNAs were identified for ALL. A ceRNA network was constructed for ALL, consisting of 845 lncRNA-miRNA and 395 miRNA–mRNA pairs. These DEmRNAs in the ceRNA network were mainly enriched in ALL-related biological processes and pathways. Ten hub genes were identified, including SMAD3, SMAD7, SMAD5, ZFYVE9, FKBP1A, FZD6, FZD7, LRP6, WNT1, and SFRP1. According to Real-time qPCR, eight lncRNAs including ATP11A-AS1, ITPK1-AS1, ANO1-AS2, CRNDE, MALAT1, CACNA1C-IT3, PWRN1, and WT1-AS were significantly upregulated in ALL bone marrow samples compared to normal samples.ConclusionOur results showed the lncRNA expression profiles and constructed ceRNA network in ALL. Furthermore, eight lncRNAs including ATP11A-AS1, ITPK1-AS1, ANO1-AS2, CRNDE, MALAT1, CACNA1C-IT3, PWRN1, and WT1-AS were identified. These results could provide a novel insight into the study of ALL.

Identification of novel mRNA-miRNA-lncRNA competing endogenous RNA network associated with prognosis of breast cancer

Epigenomics ◽  
2019 ◽  
Vol 11 (13) ◽  
pp. 1501-1518 ◽  
Author(s):  
Guansheng Zhong ◽  
Weiyang Lou ◽  
Minya Yao ◽  
Chengyong Du ◽  
Haiyan Wei ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Cancer Prognosis ◽  
Competing Endogenous Rna ◽  
Hub Genes ◽  
Cerna Network ◽  
Competing Endogenous Rna Network ◽  
Cancer Genome Atlas ◽  
Genome Atlas

Aim: To identify novel competing endogenous RNA (ceRNA) network related to patients prognosis in breast cancer. Materials & methods: Dysregulated mRNA based on intersection of three Gene Expression Omnibus and The Cancer Genome Atlas datasets were analyzed by bioinformatics. Results: In total 72 upregulated and 208 downregulated genes were identified. Functional analysis showed that some pathways related to cancer were significantly enriched. By means of stepwise reverse prediction and validation from mRNA to lncRNA, 19 hub genes, nine key miRNA and four key lncRNAs were identified by expression and survival analysis. Ultimately, the coexpression analysis identified RRM2-let-7a-5p- SNHG16/ MAL2 as key ceRNA subnetwork associated with prognosis of breast cancer. Conclusion: We successfully constructed a novel ceRNA network, among which each component was significantly associated with breast cancer prognosis.

scholarly journals Integrating Transcriptomics for the Identification of Potential Age-related Genes and Cells in Three Major Urogenital Cancers Across the Cancer Genome Atlas

2020 ◽  
Author(s):  
Jinlong Cao ◽  
Jianpeng Li ◽  
Xin Yang ◽  
Pan Li ◽  
Zhiqiang Yao ◽  
...  
Keyword(s):  
Differentially Expressed Genes ◽  
R Package ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Differentially Expressed ◽  
Hub Genes ◽  
Age Related ◽  
Cancer Genome Atlas ◽  
Urogenital Cancers ◽  
Genome Atlas

Abstract Background: Cancer is often defined as a disease of aging. The majority of patients with urogenital cancers are the elderly, whose clinical characteristics are greatly affected by age and aging. Here, we aimed to explore age-related biological changes in three major urogenital cancers by integrative bioinformatics analysis.Methods: First, mRNA (count format) and clinical data for bladder cancer, prostate cancer and renal cell carcinoma were downloaded from the Cancer Genome Atlas (TCGA) portal. The expressions of 64 cells were obtained by xCell deconvolution method. EdgeR package and limma package were used to analyze differentially expressed genes and cells in the young group and the old group, respectively. ClusterProfiler R package and clueGO plugin were used for enrichment analysis, and cytohubba plugin was used for hub genes analysis. Then co-expression analysis and chromosome distribution for hub genes were analyzed and demonstrated by RIdeogram R package. The clinical correlation of hub genes and key cells was analyzed by Graphpad Prism software. Finally, the correlation between hub genes and key cells was explored by corrplot R package.Results: We screened and identified 14 hub genes and 4 key cells related to age and urogenital cancers. The age-related differentially expressed genes and co-expressed genes were mainly enriched in muscle movement (Cl-, Ca2+), inflammatory response, antibacterial humoral immune response, substance metabolism and transport, redox reaction, etc. Most of the age-related genes are on chromosome 17. Moreover, the correlation between cells and genes was analyzed. Conclusion: Our study analyzed age-related genes and cells in the tumor microenvironment of urogenital cancers, and explored the pathways involved. This could contribute to personalized therapy for patients of different ages and a new understanding of the potential relationship between the aging microenvironment and urogenital cancers.

scholarly journals LINC00467 Is Upregulated by DNA Copy Number Amplification and Hypomethylation and Shows ceRNA Potential in Lung Adenocarcinoma

2022 ◽  
Vol 12 ◽  
Author(s):  
Wen Wang ◽  
Hao Bo ◽  
Yumei Liang ◽  
Guoli Li
Keyword(s):  
Lung Adenocarcinoma ◽  
Copy Number ◽  
Target Genes ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Dna Copy Number ◽  
Cerna Network ◽  
Cancer Genome Atlas ◽  
Copy Number Amplification ◽  
Genome Atlas

Lung adenocarcinoma (LUAD) is the most common histological lung cancer, and it is the leading cause of cancer-related deaths worldwide. Long noncoding RNAs (lncRNAs) have been implicated in tumorigenesis. LINC00467 is a novel lncRNA that is abnormally expressed in several cancer types including LUAD. However, its function and regulatory mechanism in LUAD progression remain unclear. In this study, based on The Cancer Genome Atlas data mining, we demonstrated that DNA copy number amplification and hypomethylation was positively correlated with LINC00467 expression in LUAD. In addition, DNA copy number amplification was significantly associated with distant metastasis, immune infiltration and poor survival. Microarray analysis demonstrated that LINC00467 knockdown in the LUAD A549 cell line led to a distinct microRNA expression profile that impacted various target genes involved in multiple biological processes. This finding suggests that LINC00467 may regulate LUAD progression by functioning as a competing endogenous RNA (ceRNA). Finally, we constructed a ceRNA network that included two microRNAs (hsa-miR-1225-5p, hsa-miR-575) and five mRNAs (BARX2, BCL9, KCNK1, KIAA1324, TMEM182) specific to LINC00467 in LUAD. Subsequent Kaplan-Meier survival analysis in both The Cancer Genome Atlas and Gene Expression Omnibus databases revealed that two genes, BARX2 and BCL9, were potential prognostic biomarkers for LUAD patients. In conclusion, our data provide possible mechanisms underlying the abnormal upregulation of LINC00467 as well as a comprehensive view of the LINC00467-mediated ceRNA network in LUAD, thereby highlighting its potential role in diagnosis and therapy.

Aberrantly methylated-differentially expressed genes and pathways in Epstein–Barr virus-associated gastric cancer

2020 ◽  
Vol 16 (6) ◽  
pp. 187-197
Author(s):  
Jing-jing Jing ◽  
Hao Li ◽  
Ze-yang Wang ◽  
Heng Zhou ◽  
Li-ping Sun ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Differentially Expressed Genes ◽  
Epstein Barr Virus ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Hub Genes ◽  
Barr Virus ◽  
Cancer Genome Atlas ◽  
Epstein Barr ◽  
Genome Atlas

Aim: To identify the methylated-differentially expressed genes (MDEGs) that may serve as diagnostic markers and therapeutic targets in Epstein–Barr virus-associated gastric cancer (EBVaGC) and to explore the methylation-based pathways for elucidating biological mechanisms of EBVaGC. Materials & methods: Gene expression and methylation profiles were downloaded from GEO database. MDEGs were identified by GEO2R. Pathway enrichment analyses were conducted based on DAVID database. Hub genes were identified by Cytoscape, which were further verified by The Cancer Genome Atlas database. Results: A total of 367 hypermethylated, lowly expressed genes were enriched in specific patterns of cell differentiation. 31 hypomethylated, highly expressed genes demonstrated enrichment in regulation of immune system process. After validation using The Cancer Genome Atlas database, seven genes were confirmed to be significantly different hub genes in EBVaGC. Conclusion: EBVaGC-specific MDEGs and pathways can be served as potential biomarkers for precise diagnosis and treatment of EBVaGC and provide novel insights into the mechanisms involved.

scholarly journals lncRNA-miRNA-mRNA ceRNA Network in Thyroid Carcinoma from The Cancer Genome Atlas

2020 ◽  
Author(s):  
Guoheng Mo ◽  
Qunguang Jiang ◽  
Zixuan Wang ◽  
Zhaoting Zheng ◽  
XiaoSi Chen
Keyword(s):  
Papillary Thyroid Carcinoma ◽  
Thyroid Carcinoma ◽  
Molecular Mechanisms ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Differentially Expressed ◽  
Papillary Thyroid ◽  
Cerna Network ◽  
Cancer Genome Atlas ◽  
Genome Atlas

Abstract Increasing evidence indicates that the competitive endogenous RNA (ceRNA) hypothesis, that is, long non-coding RNA (LncRNA) can competitively bind microRNA (miRNA) through miRNA response elements to affect the expression of target RNA, and dysregulation of LncRNA expression plays a key role in tumor progression. The papillary thyroid carcinoma that we studied is the most significant pathological type of thyroid cancer, but its ceRNA network has not been extensively evaluated. We analyzed level-3 data from RNA-Seq of 58 para-carcinoma tissues and 501 patients with primary papillary thyroid carcinoma (PTC) using the DEseq software package and downloaded clinical information from The Cancer Genome Atlas (TCGA) to find potential biomarkers or therapeutic targets. As a result, 149 differential miRNAs were selected, including 117 up -regulated, 32 down-regulated, and 3099 differential mRNAs, including 1976 up-regulated, 1123 down-regulated, and 434 differential lncRNAs, including 331 up-regulated and 103 down-regulated (Fold Change > 2, P < 0.05). The interactions between these differentially expressed RNA groups constitute the ceRNA network of PTC. Moreover, we used the microde database to predict the miRNAs that may be acted by the above screened differential lncRNAs and intersected with the selected miRNAs, and further predicted the target genes of the intersecting miRNAs by TargetScan, miRTarBase and miRDB, and intersected with the selected mRNAs. From the constructed ceRNA network we can see that Linc00460 may cause the invasion and metastasis of PTC by competitively inhibiting hsa-mir-150 and upregulating the expression of its downstream target gene EREG. Our study identified a series of lncRNAs associated with PTC progression and prognosis, and this complex ceRNA interaction network provides guidance for better understanding of the molecular mechanisms of PTC and can be used as an effective diagnostic tool for PTC invasion, metastasis and prognosis. Kaplan-Meier analysis of the differentially expressed RNAs associated with PTC pathogenesis confirmed that the lncRNAs AC097717.1, C20orf203, EMX2OS were potentially associated with the prognosis of PTC (P<0.05).

scholarly journals Association Between Obesity and Incident Colorectal Cancer: An Analysis Based on Colorectal Cancer Database in the Cancer Genome Atlas

2021 ◽  
Author(s):  
Su Yongxian ◽  
Chen Tonghua
Keyword(s):  
Colorectal Cancer ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Obese Group ◽  
Pathway Enrichment Analysis ◽  
Ppi Network ◽  
Hub Genes ◽  
Significant Difference ◽  
Cancer Genome Atlas ◽  
Genome Atlas

Abstract Background To investigate gene factors of colorectal cancer (CRC) in obesity and potential molecular markers. Methods Clinical data and mRNA expression data from The Cancer Genome Atlas (TCGA) was collected and divided into obese group and non-obese group according to BMI. The differential expressed genes (DEGs) were screened out by “Limma” package of R software based on (|log2(fold change)|>2 and p < 0.05). The functions of DEGs were revealed with Gene Ontology and Kyoto Encyclopedia Genes and Genomes pathway enrichment analysis using the DAVID database. Then STRING database and Cytoscape were used to construct a protein-protein interaction (PPI) network and identify hub genes. Kaplan-Meier analysis was used to assess the potential prognostic genes for CRC patients. Results It has revealed 2055 DEGs in obese group with CRC, 7615 DEGs in non-obese group and 9046 DEGs in total group. MS4A12, TMIGD1, CA2, GBA3 and SLC51B were the top five downregulated genes in obese group. A PPI network consisted of 1042 nodes and 4073 edges, and top ten hub genes SST, PYY, GNG12, CCL13, MCHR2, CCL28, ADCY9, SSTR1, CXCL12 and ADRA2A were identified in obese group. PDCD11 may well predict overall survivals of CRC patients in non-obese group. The survival time of obese group was shorter than that of non-obese group, but there was no significant difference. Conclusions PDCD11 may be a potential molecular marker for non-obese patients with CRC.

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