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Integrated cohort of esophageal squamous cell cancer reveals genomic features underlying clinical characteristics

Author

Listed:
  • Minghao Li

    (Shandong University)

  • Zicheng Zhang

    (The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine
    Shandong First Medical University and Shandong Academy of Medical Sciences)

  • Qianrong Wang

    (The Third Affiliated Hospital of Shandong First Medical University)

  • Yan Yi

    (Shandong First Medical University and Shandong Academy of Medical Sciences)

  • Baosheng Li

    (Shandong University
    Shandong First Medical University and Shandong Academy of Medical Sciences)

Abstract

Esophageal squamous cell cancer (ESCC) is the major pathologic type of esophageal cancer in Asian population. To systematically evaluate the mutational features underlying clinical characteristics, we establish the integrated dataset of ESCC-META that consists of 1930 ESCC genomes from 33 datasets. The data process pipelines lead to well homogeneity of this integrated cohort for further analysis. We identified 11 mutational signatures in ESCC, some of which are related to clinical features, and firstly detect the significant mutated hotspots in TGFBR2 and IRF2BPL. We screen the survival related mutational features and found some genes had different prognostic impacts between early and late stage, such as PIK3CA and NFE2L2. Based on the results, an applicable approach of mutational score is proposed and validated to predict prognosis in ESCC. As an open-sourced, quality-controlled and updating mutational landscape, the ESCC-META dataset could facilitate further genomic and translational study in this field.

Suggested Citation

  • Minghao Li & Zicheng Zhang & Qianrong Wang & Yan Yi & Baosheng Li, 2022. "Integrated cohort of esophageal squamous cell cancer reveals genomic features underlying clinical characteristics," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
    • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-32962-1
    DOI: 10.1038/s41467-022-32962-1
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    Cited by:

    1. De-Chen Lin, 2023. "Large-scale genomic analyses reveal alterations and mechanisms underlying clonal evolution and immune evasion in esophageal cancer," Nature Communications, Nature, vol. 14(1), pages 1-3, December.

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