Department of Pathology & Shanxi Key Laboratory of Carcinogenesis and Translational Research on Esophageal Cancer, Shanxi Medical University, Taiyuan, Shanxi, 030001, China.
State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.
Cell Res. 2020 Oct;30(10):902-913. doi: 10.1038/s41422-020-0333-6. Epub 2020 May 12.
Esophageal squamous cell carcinoma (ESCC) is a poor-prognosis cancer type with limited understanding of its molecular etiology. Using 508 ESCC genomes, we identified five novel significantly mutated genes and uncovered mutational signature clusters associated with metastasis and patients' outcomes. Several functional assays implicated that NFE2L2 may act as a tumor suppressor in ESCC and that mutations in NFE2L2 probably impaired its tumor-suppressive function, or even conferred oncogenic activities. Additionally, we found that the NFE2L2 mutations were significantly associated with worse prognosis of ESCC. We also identified potential noncoding driver mutations including hotspot mutations in the promoter region of SLC35E2 that were correlated with worse survival. Approximately 5.9% and 15.2% of patients had high tumor mutation burden or actionable mutations, respectively, and may benefit from immunotherapy or targeted therapies. We found clinically relevant coding and noncoding genomic alterations and revealed three major subtypes that robustly predicted patients' outcomes. Collectively, we report the largest dataset of genomic profiling of ESCC useful for developing ESCC-specific biomarkers for diagnosis and treatment.
食管鳞状细胞癌（ESCC）是一种预后不良的癌症类型，对其分子病因学的了解有限。本研究使用 508 个 ESCC 基因组，鉴定了五个新的显著突变基因，并揭示了与转移和患者预后相关的突变特征簇。几项功能分析表明，NFE2L2 可能在 ESCC 中作为肿瘤抑制因子发挥作用，而 NFE2L2 的突变可能削弱其肿瘤抑制功能，甚至赋予致癌活性。此外，我们发现 NFE2L2 突变与 ESCC 的预后不良显著相关。我们还鉴定了潜在的非编码驱动突变，包括 SLC35E2 启动子区域的热点突变，这些突变与更差的生存相关。约 5.9%和 15.2%的患者分别具有高肿瘤突变负荷或可操作的突变，可能受益于免疫治疗或靶向治疗。我们发现了具有临床意义的编码和非编码基因组改变，并揭示了三个主要的亚型，这些亚型能够稳健地预测患者的预后。总之，我们报告了 ESCC 最大的基因组分析数据集，有助于开发用于诊断和治疗的 ESCC 特异性生物标志物。
