MicroRNA-Related Prognosis Biomarkers from High-Throughput Sequencing Data of Colorectal Cancer.

Background. Colorectal cancer (CRC) is the third most common cancer in the world, and most of them are adenocarcinomas. CRC could be classified as colon adenocarcinoma (COAD) and rectum adenocarcinoma (READ) according to the original tumorigenesis position. Increasing evidences indicated that microR...

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Publicado en:BioMed Research International pp. 1 - 13
Autores principales: Xing, Xiao-Liang, Yao, Zhi-Yong, Zhang, Ti, Zhu, Ning, Liu, Yuan-Wu, Peng, Jing
Formato: pictorial research tables/charts Journal Article
Publicado: Wiley-Blackwell 9/10/2020
Acceso en línea:Ver este registro en EBSCOhost
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      dt: 9/10/2020
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      pub: Wiley-Blackwell
      place: Malden, Massachusetts
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        10.1155/2020/7905380
        145670997
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      tig:
        atl: MicroRNA-Related Prognosis Biomarkers from High-Throughput Sequencing Data of Colorectal Cancer.
      aug:
        au:
          Xing, Xiao-Liang
          Yao, Zhi-Yong
          Zhang, Ti
          Zhu, Ning
          Liu, Yuan-Wu
          Peng, Jing
        affil: Xiangya Hospital, Central South University, Changsha, 410078 Hunan, China
      sug:
        subj:
          MicroRNA Analysis
          Biological Markers Analysis
          Sequence Analysis
          Colorectal Neoplasms Prognosis
          Human
          Gene Expression
          Data Analysis Software
          Colorectal Neoplasms Familial and Genetic
          Survival Analysis
          Descriptive Statistics
          Comparative Studies
          Cancer Patients
      ab: Background. Colorectal cancer (CRC) is the third most common cancer in the world, and most of them are adenocarcinomas. CRC could be classified as colon adenocarcinoma (COAD) and rectum adenocarcinoma (READ) according to the original tumorigenesis position. Increasing evidences indicated that microRNAs (miRNAs) play an important role in the occurrence of multiple tumors. Methods. In this study, we firstly downloaded miRNA (COAD, 8 controls vs. 455 tumors; READ, 3 controls vs. 161 tumors) and mRNA (COAD, 41 controls vs. 478 tumors; READ, 10 controls vs. 166 tumors) data from The Cancer Genome Atlas (TCGA) database and then used DESeq2, RegParallel, miRDB, TargetScanHuman 7.2, DAVID 6.8, STRING, and Cytoscape software to identify the potential prognosis biomarkers. Results. We identified 175 differential expression miRNAs (DEMs) and 3747 differential expression genes (DEGs) in COAD and 184 DEMs and 3928 DEGs in READ. And then, we obtained 21 (13 in COAD and 8 in READ) DEMs associated with the survival rates, which correlated with 440 (217 in COAD and 223 in READ) overlapping DEGs. Through survival analysis for those overlapping DEGs, we found 11 (8 in COAD and 3 in READ) overlapping DGEs associated with survival rates of patients, which were correlated with 9 (7 in COAD and 2 in READ) DEMs significantly. Conclusion. In this study, we found several candidate prognostic biomarkers which have been identified in various cancers and also found several new prognosis biomarkers of COAD and READ. In conclusion, this analysis based on theoretical knowledge and clinical outcomes we have done needs further confirmation by more researches.
      pubtype: Academic Journal
      doctype:
        pictorial
        research
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        Journal Article
      ougenre: Article
    language: English
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