24 / 2026-02-28 08:06:53
Proteomic subtypes enrich current acute myeloid leukemia nomenclature and reflect intrinsic pathogenesis alongside aging
Acute myeloid leukemia (AML),proteomics,aging,classification,prognosis
摘要待审
王震毅 / 上海交通大学医学院附属瑞金医院
Acute myeloid leukemia (AML) is a highly heterogeneous hematological malignancy that increasingly affects the older population, with its posttranscriptional landscape remaining largely elusive. Establishing a stable proteomics-based classification system and systematically screening age-related proteins and regulatory networks are crucial for understanding the pathogenesis and outcomes of AML. In this study, we leveraged a multiomics cohort of 374 patients newly diagnosed with AML, integrating proteome, phosphoproteome, genome, transcriptome, and drug screening data. Through similarity network fusion clustering, we established 8 proteomic subtypes with distinct clinical and molecular properties, including S1 (CEBPA mutations), S3 (myelodysplasia-related AML), S4 (PML::RARA), S5 (NPM1 mutations), S6 (PML::RARA and RUNX1::RUNX1T1), S8 (CBFB::MYH11), S2 and S7 (mixed), aligning well with and adding actionable value to the latest World Health Organization nomenclature of AML. Hematopoietic lineage profiling of proteins indicated that megakaryocyte/platelet- and immune-related networks characterized distinct aging patterns in AML, which were consistent with our recent findings at the RNA level. Phosphosites also demonstrated distinct age-related features. The high protein abundance of megakaryocytic signatures was observed in S2, S3, and S7 subtypes, which were associated with advanced age and dismal prognosis of patients. A hematopoietic aging score with an independent prognostic value was established based on proteomic data, where higher scores correlated with myelodysplasia-related AML, NPM1 mutations, and clonal hematopoiesis-related gene mutations. Collectively, this study provides an overview of the molecular circuits and regulatory networks of AML during the aging process, advancing current classification systems and offering a comprehensive perspective on the disease.
重要日期
  • 会议日期

    03月27日

    2026

    03月29日

    2026

  • 03月09日 2026

    初稿截稿日期

  • 03月29日 2026

    注册截止日期

主办单位
中国生物信息学会基因组信息学专业委员会
承办单位
西湖大学
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