The Cancer Genome Atlas (TCGA)データベースを利用した研究


The Cancer Genome Atlas (TCGA)とは

The Cancer Genome Atlas (TCGA) provides researchers with unprecedented amounts of molecular data along with clinical and histopathological information (http:// This data set has not only led to increases in our understanding of cancer (Ciriello et al., 2013; Hoadley et al., 2014), but its scale has also allowed for previously impossible projects such as a comprehensive cataloguing of the human transcriptome (Han et al., 2014; Iyer et al., 2015).

(OncoLnc: linking TCGA survival data to mRNAs, miRNAs, and lncRNAs Jordan Anaya)



  1. Comprehensive Review of Web Servers and Bioinformatics Tools for Cancer Prognosis Analysis Front. Oncol., 05 February 2020 |


  1. Working with TCGAbiolinks package




  1. CIBERSORT analysis of TCGA and METABRIC identifies subgroups with better outcomes in triple negative breast cancer Kelly E. Craven, Yesim Gökmen-Polar & Sunil S. Badve Scientific Reports volume 11, Article number: 4691 (2021) Published: 25 February 2021
  2. Genomic Characteristics of Triple-Negative Breast Cancer Nominate Molecular Subtypes That Predict Chemotherapy Response Jihyun Kim, Doyeong Yu, Youngmee Kwon, Keun Seok Lee, Sung Hoon Sim, Sun-Young Kong, Eun Sook Lee, In Hae Park and Charny Park DOI: 10.1158/1541-7786.Molecular Cancer Research. MCR-19-0453 Published February 2020
  3. Integrative analysis of breast cancer profiles in TCGA by TNBC subgrouping reveals novel microRNA-specific clusters, including miR-17-92a, distinguishing basal-like 1 and basal-like 2 TNBC subtypes Karel Kalecky, Rebecca Modisette, Samantha Pena, Young-Rae Cho & Joseph Taube BMC Cancer volume 20, Article number: 141 (2020)
  4. Genomic and Transcriptomic Landscape of Triple-Negative Breast Cancers: Subtypes and Treatment Strategies (2019)
  5. Translational Oncology Volume 11, Issue 2, April 2018, Pages 311-329 Translational Oncology A Comprehensive Immunologic Portrait of Triple-Negative Breast Cancer


  1. Exploring TCGA database for identification of potential prognostic genes in stomach adenocarcinoma Lin Zhou, Wei Huang, He-Fen Yu, Ya-Juan Feng & Xu Teng Cancer Cell International volume 20, Article number: 264 (2020) Published: 23 June 2020


  1. Identification of key genes and pathways by bioinformatics analysis with TCGA RNA sequencing data in hepatocellular carcinoma Authors: Qiandong Zhu Yunpeng Sun Qingqing Zhou Qikuan He Haixin Qian View Affiliations Published online on: September 27, 2018



  1. Identification of Key Genes and Pathways in Triple-Negative Breast Cancer by Integrated Bioinformatics Analysis. Volume 2018 |Article ID 2760918 | これはマイクロアレイデータの解析