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Refining prognostic assessment of diffuse large B-cell lymphoma: insights from multi-omics and single-cell analysis unveil SRM as a key target for regulating immunotherapy

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机构: [1]Capital Med Univ, Beijing Tongren Hosp, Dept Hematol, Beijing 100730, Peoples R China [2]Southern Med Univ, Nanfang Hosp, Dept Hematol, Guangzhou 510515, Peoples R China [3]Guangdong Med Univ, Sch Clin Med 1, Zhanjiang 524000, Peoples R China
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关键词: DLBCL Proliferation Stromal Immune Risk stratification SRM TME Immunotherapy

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Purposes Previous studies have demonstrated that proliferation, stroma or immunity strongly influence the prognosis and therapeutic resistance of diffuse large B-cell lymphoma (DLBCL). Herein, we aimed to integrate proliferation, stromal, and immune (PSI) features to systematically evaluate the risk stratification and explore novel therapeutic targets in DLBCL. MethodsUsing data from multiple researches, we comprehensively evaluated the characteristics and prognostic impact of PSI features in DLBCL, and developed a novel risk stratification model (PSI score) with a consistent cutoff value to stratify the risk of 3,229 DLBCL patients from different cohorts. Mechanisms underlying adverse prognosis in the high-risk DLBCLs were investigated through transcriptomic (n = 3,229), genomic (n = 576), and scRNA-seq (n = 20) analyses. ResultsWe identified a high-risk DLBCL subgroup (HPSI, 36.1% of DLBCL). HPSI was characterized by upregulation of spermidine synthase (SRM) and cold tumor microenvironment (TME). Compared to low-risk group, HPSI exhibited poorer prognosis, with lower 3-year OS (51.7% vs. 78.1%, P < 0.0001) and PFS (48.9% vs. 72.6%, P < 0.0001) rates. HPSI shared malignant proliferative phenotype resembling Burkitt lymphoma. Genomic analysis revealed extensive copy-number loss in the chemokine and interleukin coding regions within HPSI. Bulk and scRNA-seq analyses indicated that upregulation of SRM might mediate cold TME in DLBCL, potentially through suppressing immune activation pathways, promoting dendritic cells (DCs) transformation into tolerogenic DCs, and facilitating M2 polarization of macrophages. Finally, for eventual clinical translation, we integrated the model with other clinical features to develop a comprehensive database for DLBCL. ConclusionOur study effectively simplifies risk stratification of DLBCL, revealing that immune microenvironment and SRM jointly shape a subgroup of DLBCL with extremely poor prognosis. Targeting SRM may become a potential strategy for modulating immunotherapy in DLBCL, providing new insight for immunotherapy.

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出版当年[2025]版:
大类 | 2 区 计算机科学
小类 | 2 区 计算机:理论方法
最新[2025]版:
大类 | 2 区 计算机科学
小类 | 2 区 计算机:理论方法
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出版当年[2023]版:
Q1 COMPUTER SCIENCE, THEORY & METHODS
最新[2023]版:
Q1 COMPUTER SCIENCE, THEORY & METHODS

影响因子: 最新[2023版] 最新五年平均 出版当年[2023版] 出版当年五年平均 出版前一年[2022版]

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第一作者机构: [1]Capital Med Univ, Beijing Tongren Hosp, Dept Hematol, Beijing 100730, Peoples R China
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