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A transcriptome based molecular classification scheme for cholangiocarcinoma and subtype-derived prognostic biomarker

Author

Listed:
  • Zhongqi Fan

    (The First Hospital of Jilin University)

  • Xinchen Zou

    (Peking University Medical Industrial Park, Zhongguancun Life Science Park)

  • Guangyi Wang

    (The First Hospital of Jilin University)

  • Yahui Liu

    (The First Hospital of Jilin University)

  • Yanfang Jiang

    (The First Hospital of Jilin University)

  • Haoyan Wang

    (Peking University Medical Industrial Park, Zhongguancun Life Science Park)

  • Ping Zhang

    (The First Hospital of Jilin University)

  • Feng Wei

    (The First Hospital of Jilin University)

  • Xiaohong Du

    (The First Hospital of Jilin University)

  • Meng Wang

    (The First Hospital of Jilin University)

  • Xiaodong Sun

    (The First Hospital of Jilin University)

  • Bai Ji

    (The First Hospital of Jilin University)

  • Xintong Hu

    (The First Hospital of Jilin University)

  • Liguo Chen

    (The First Hospital of Jilin University)

  • Peiwen Zhou

    (The First Hospital of Jilin University)

  • Duo Wang

    (The First Hospital of Jilin University)

  • Jing Bai

    (Peking University Medical Industrial Park, Zhongguancun Life Science Park)

  • Xiao Xiao

    (Geneplus-Shenzhen, No.14 Zhongxing Road, Pingshan District)

  • Lijiao Zuo

    (Peking University Medical Industrial Park, Zhongguancun Life Science Park)

  • Xuefeng Xia

    (Peking University Medical Industrial Park, Zhongguancun Life Science Park)

  • Xin Yi

    (Peking University Medical Industrial Park, Zhongguancun Life Science Park
    Xi’an Jiaotong University)

  • Guoyue Lv

    (The First Hospital of Jilin University)

Abstract

Previous studies on the molecular classification of cholangiocarcinoma (CCA) focused on certain anatomical sites, and disregarded tissue contamination biases in transcriptomic profiles. We aim to provide universal molecular classification scheme and prognostic biomarker of CCAs across anatomical locations. Comprehensive bioinformatics analysis is performed on transcriptomic data from 438 CCA cases across various anatomical locations. After excluding CCA tumors showing normal tissue expression patterns, we identify two universal molecular subtypes across anatomical subtypes, explore the molecular, clinical, and microenvironmental features of each class. Subsequently, a 30-gene classifier and a biomarker (called “CORE-37”) are developed to predict the molecular subtype of CCA and prognosis, respectively. Two subtypes display distinct molecular characteristics and survival outcomes. Key findings are validated in external cohorts regardless of the stage and anatomical location. Our study provides a CCA classification scheme that complements the conventional anatomy-based classification and presents a promising prognostic biomarker for clinical application.

Suggested Citation

  • Zhongqi Fan & Xinchen Zou & Guangyi Wang & Yahui Liu & Yanfang Jiang & Haoyan Wang & Ping Zhang & Feng Wei & Xiaohong Du & Meng Wang & Xiaodong Sun & Bai Ji & Xintong Hu & Liguo Chen & Peiwen Zhou & D, 2024. "A transcriptome based molecular classification scheme for cholangiocarcinoma and subtype-derived prognostic biomarker," Nature Communications, Nature, vol. 15(1), pages 1-14, December.
  • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-44748-8
    DOI: 10.1038/s41467-024-44748-8
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    1. Kosuke Yoshihara & Maria Shahmoradgoli & Emmanuel Martínez & Rahulsimham Vegesna & Hoon Kim & Wandaliz Torres-Garcia & Victor Treviño & Hui Shen & Peter W. Laird & Douglas A. Levine & Scott L. Carter , 2013. "Inferring tumour purity and stromal and immune cell admixture from expression data," Nature Communications, Nature, vol. 4(1), pages 1-11, December.
    2. Yujin Hoshida, 2010. "Nearest Template Prediction: A Single-Sample-Based Flexible Class Prediction with Confidence Assessment," PLOS ONE, Public Library of Science, vol. 5(11), pages 1-8, November.
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