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Comprehensive Analysis of Single-cell and Bulk Transcriptomics Identified Regulatory T-cell Features as Predictors of Prognosis in Diffuse Large B-cell Lymphoma

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NIAID Data Ecosystem2026-05-02 收录
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https://zenodo.org/record/14722770
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Diffuse large B-cell lymphoma (DLBCL) is a biologically and clinically heterogeneous malignancy. Advances in transcriptomic and genetic profiling have significantly enhanced our understanding of the disease's intrinsic pathogenesis, uncovering numerous potential therapeutic targets. However, the impact of tumor-infiltrating Regulatory T cells (Tregs) on the prognosis of DLBCL remains controversial. Here, we developed a Treg-associated gene signature by integrating single-cell and bulk transcriptome data to predict the prognosis of DLBCL patients receiving standard immunochemotherapy. In total, 227 Tregs feature genes were identified, six of which were selected for constructing a prognostic signature. DLBCL patients possessing high-risk scores had significantly poorer survival outcomes than those who possess low-risk scores in NCICCR and validation cohorts. Mutations in PIM1, MYD88, DTX1, CARD11, CD79B, ETV6, BCL6, and CDKN2A were predominantly observed in the high-risk group, whereas alterations in TNFRSF14 and DNMT3A were more frequently detected in the low-risk group. Immune infiltration analysis revealed that the high-risk group exhibited an immunosuppressive microenvironment, whereas the low-risk group showed a higher abundance of non-cellular components in the tumor microenvironment (TME). Finally, a gene signature constructed from Treg markers TNFRSF25 and SELL can effectively predict long-term responsiveness to Axicabtagene Ciloleucel (Axi-cel) therapy. In summary, our study developed a prognostic signature consisting of six Treg feature genes by integrating single-cell and bulk transcriptomics to predict clinical outcomes in DLBCL patients. The risk signature was significantly associated with immunological characteristics, and our additional findings suggest that the expression levels of TNFRSF25 and SELL could serve as novel biomarkers for predicting response to Axi-cel treatment.
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2025-02-05
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