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阐明T细胞受体库在骨髓增生异常肿瘤和急性髓系白血病中的作用。

Elucidating the Role of the T Cell Receptor Repertoire in Myelodysplastic Neoplasms and Acute Myeloid Leukemia.

作者信息

Barakos Georgios Petros, Georgoulis Vasileios, Koumpis Epameinondas, Hatzimichael Eleftheria

机构信息

First Department of Internal Medicine, General Hospital of Piraeus "Tzaneio", 18536 Piraeus, Greece.

Department of Haematology, Faculty of Medicine, School of Health Sciences, University of Ioannina, 45500 Ioannina, Greece.

出版信息

Diseases. 2025 Jan 17;13(1):19. doi: 10.3390/diseases13010019.

DOI:10.3390/diseases13010019
PMID:39851483
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11765071/
Abstract

T cells, as integral components of the adaptive immune system, recognize diverse antigens through unique T cell receptors (TCRs). To achieve this, during T cell maturation, the thymus generates a wide repertoire of TCRs. This is essential for understanding cancer evolution, progression, and the efficacy of immunotherapies. Myelodysplastic neoplasms (MDS) and acute myeloid leukemia (AML) are hematological neoplasms that are characterized by immune evasion mechanisms, with immunotherapy giving only modest results thus far. Our review of TCR repertoire dynamics in these diseases reveals distinct patterns: MDS patients show increased TCR clonality with disease progression, while AML exhibits varied TCR signatures depending on disease stage and treatment response. Understanding these patterns has important clinical implications, as TCR repertoire metrics may serve as potential biomarkers for disease progression and treatment response, particularly in the context of immunotherapy and stem cell transplantation. These insights could guide patient stratification and treatment selection, ultimately improving therapeutic outcomes in MDS and AML.

摘要

T细胞作为适应性免疫系统的重要组成部分,通过独特的T细胞受体(TCR)识别多种抗原。为实现这一点,在T细胞成熟过程中,胸腺产生了广泛的TCR库。这对于理解癌症的演变、进展以及免疫疗法的疗效至关重要。骨髓增生异常肿瘤(MDS)和急性髓系白血病(AML)是血液系统肿瘤,其特征为免疫逃逸机制,迄今为止免疫疗法仅取得了有限的效果。我们对这些疾病中TCR库动态变化的综述揭示了不同的模式:MDS患者的TCR克隆性随疾病进展而增加,而AML则根据疾病阶段和治疗反应表现出不同的TCR特征。了解这些模式具有重要的临床意义,因为TCR库指标可能作为疾病进展和治疗反应的潜在生物标志物,特别是在免疫疗法和干细胞移植的背景下。这些见解可以指导患者分层和治疗选择,最终改善MDS和AML的治疗效果。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c11c/11765071/a34c16d16f69/diseases-13-00019-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c11c/11765071/48207e5612c0/diseases-13-00019-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c11c/11765071/a0479e63360c/diseases-13-00019-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c11c/11765071/a34c16d16f69/diseases-13-00019-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c11c/11765071/48207e5612c0/diseases-13-00019-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c11c/11765071/a0479e63360c/diseases-13-00019-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c11c/11765071/a34c16d16f69/diseases-13-00019-g003.jpg

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本文引用的文献

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BertTCR: a Bert-based deep learning framework for predicting cancer-related immune status based on T cell receptor repertoire.BertTCR:一种基于 Bert 的深度学习框架,用于基于 T 细胞受体库预测癌症相关的免疫状态。
Brief Bioinform. 2024 Jul 25;25(5). doi: 10.1093/bib/bbae420.
2
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Int Immunopharmacol. 2024 Sep 10;138:112376. doi: 10.1016/j.intimp.2024.112376. Epub 2024 Jun 24.
3
The Deep Learning Framework iCanTCR Enables Early Cancer Detection Using the T-cell Receptor Repertoire in Peripheral Blood.
深度学习框架 iCanTCR 利用外周血中的 T 细胞受体库进行早期癌症检测。
Cancer Res. 2024 Jun 4;84(11):1915-1928. doi: 10.1158/0008-5472.CAN-23-0860.
4
T-cell dysfunctions in myelodysplastic syndromes.骨髓增生异常综合征中的 T 细胞功能障碍。
Blood. 2024 Apr 4;143(14):1329-1343. doi: 10.1182/blood.2023023166.
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TCRs and AI: the future is now.T细胞受体与人工智能:未来已来。
Nat Rev Immunol. 2024 Jan;24(1):3. doi: 10.1038/s41577-023-00974-7.
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γδ T cells: origin and fate, subsets, diseases and immunotherapy.γδ T 细胞:起源与命运、亚群、疾病与免疫治疗。
Signal Transduct Target Ther. 2023 Nov 22;8(1):434. doi: 10.1038/s41392-023-01653-8.
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