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.

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 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.

scholarly journals Identification and Potential Mechanisms of a 7-MicroRNA Signature That Predicts Prognosis in Patients with Lower-Grade Glioma

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Zhizheng Liu ◽  
Hongliang Meng ◽  
Miaoxian Fang ◽  
Wenlong Guo
Keyword(s):  
Signaling Pathway ◽  
Predictive Accuracy ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Differentially Expressed ◽  
Lower Grade ◽  
Clinical Practices ◽  
Lower Grade Glioma ◽  
Cancer Genome Atlas ◽  
Genome Atlas

Background. Lower-grade glioma is an intracranial cancer that may develop into glioblastoma with high mortality. The main objective of our study is to develop microRNA for LGG patients which will provide novel prognostic biomarkers along with therapeutic targets. Methods. Clinicopathological data of LGG patients and their RNA expression profile were downloaded through The Cancer Genome Atlas Relevant expression profiles of RNA, and clinicopathological data of the LGG patients had been extracted from the database of “The Cancer Genome Atlas.” Differential expression analysis had been conducted for identification of the differentially expressed microRNAs as well as mRNAs in LGG samples and normal ones. ROC curves and K–M plots were plotted to confirm performance and for predictive accuracy. For the confirmation of microRNAs as an independent prognostic factor, an independent prognosis analysis was conducted. Moreover, target differentially expressed genes of these identified prognostic microRNAs that were extracted and protein-protein interaction networks were developed. Moreover, the biological functions of signature were determined through Genome Ontology analysis, genome pathway analysis, and Kyoto Encyclopedia of Genes. Results. 7-microRNA signature was identified that has the ability of categorization of individuals with LGG into high- and low-risk groups on the basis of significant difference in survival during training and testing cohorts (P < 0.001). The 7-microRNA signature had appeared to be robust in predictive accuracy (all AUC> 0.65). It was also approved with multivariate Cox regression along with some traditional clinical practices that we can use 7-microRNA signature for therapeutic purposes as a self-regulating predictive OS factor (P < 0.001). KEGG and Gene Ontology (GO) analyses reported that 7-microRNAs had mainly developed in important pathways related with glioma, e.g., the “cAMP signaling pathway,” “glutamatergic synapses,” and “calcium signaling pathway”. Conclusion. A newly discovered 7-microRNA signature could be a potential target for the diagnosis and treatment for LGG patients.

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.

scholarly journals Exceptional Chemotherapy Response in Metastatic Colorectal Cancer Associated With Hyper-Indel–Hypermutated Cancer Genome and Comutation of POLD1 and MLH1

2017 ◽  
pp. 1-12
Author(s):  
Manish R. Sharma ◽  
James T. Auman ◽  
Nirali M. Patel ◽  
Juneko E. Grilley-Olson ◽  
Xiaobei Zhao ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Colon Cancer ◽  
Somatic Mutation ◽  
Mutation Rate ◽  
Germ Line ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Response To Chemotherapy ◽  
Cancer Genome Atlas ◽  
Genome Atlas

Purpose A 73-year-old woman with metastatic colon cancer experienced a complete response to chemotherapy with dose-intensified irinotecan that has been durable for 5 years. We sequenced her tumor and germ line DNA and looked for similar patterns in publicly available genomic data from patients with colorectal cancer. Patients and Methods Tumor DNA was obtained from a biopsy before therapy, and germ line DNA was obtained from blood. Tumor and germline DNA were sequenced using a commercial panel with approximately 250 genes. Whole-genome amplification and exome sequencing were performed for POLE and POLD1. A POLD1 mutation was confirmed by Sanger sequencing. The somatic mutation and clinical annotation data files from the colon (n = 461) and rectal (n = 171) adenocarcinoma data sets were downloaded from The Cancer Genome Atlas data portal and analyzed for patterns of mutations and clinical outcomes in patients with POLE- and/or POLD1-mutated tumors. Results The pattern of alterations included APC biallelic inactivation and microsatellite instability high (MSI-H) phenotype, with somatic inactivation of MLH1 and hypermutation (estimated mutation rate > 200 per megabase). The extremely high mutation rate led us to investigate additional mechanisms for hypermutation, including loss of function of POLE. POLE was unaltered, but a related gene not typically associated with somatic mutation in colon cancer, POLD1, had a somatic mutation c.2171G>A [p.Gly724Glu]. Additionally, we noted that the high mutation rate was largely composed of dinucleotide deletions. A similar pattern of hypermutation (dinucleotide deletions, POLD1 mutations, MSI-H) was found in tumors from The Cancer Genome Atlas. Conclusion POLD1 mutation with associated MSI-H and hyper-indel–hypermutated cancer genome characterizes a previously unrecognized variant of colon cancer that was found in this patient with an exceptional response to chemotherapy.

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