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IF 2.9 2区医学 Q2 ONCOLOGY

Cancer Medicine Pub Date : 2025-03-01 DOI:10.1002/cam4.70736

Minori Tamai, Chiaki Komatsu, Keiko Kagami, Shin Kasai, Koshi Akahane, Kumiko Goi, Kanji Sugita, Chihiro Tomoyasu, Toshihiko Imamura, Hiroaki Goto, Takeshi Inukai

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引用次数: 0

摘要

背景在 B 细胞前体急性淋巴细胞白血病（BCP-ALL）中，染色体易位与预后密切相关。RNA 测序（RNA-seq）是一种功能强大的技术，它揭示了 BCP-ALL 临床样本中易位类型与基因表达模式之间的密切联系。癌症细胞系是强大的研究工具，因此，我们建立了一个更大的 BCP-ALL 细胞系系列，并进行了 RNA-seq 分析，以证实其作为模型系统的实用性。方法我们对总共94个BCP-ALL细胞系进行了RNA-seq分析，其中包括具有8种代表性易位类型的80个细胞系。结果在 UMAP 可视化分析中，融合基因的类型与基因表达模式之间存在密切联系。在基因表达谱的聚类分析中，每种类型的融合基因都与前 51 个可变基因的表达谱有明显的关联。具有重要临床意义的是，BCP-ALL 细胞系中的大多数顶级可变基因也与临床样本中的融合基因类型有显著关联。在评估67个细胞系中125个细胞周期相关基因与S期和G2/M期百分比的关联时，证实了10个细胞周期相关基因（HDAC2、CDC23、YWHAG、MAD2L1、CCNH、ANAPC7、CDC6、ANAPC5、ORC3和RBX1）与细胞周期进展呈显著正相关。此外，与诊断时建立的细胞系相比，复发时建立的细胞系中分别有 40 个和 10 个基因出现了明显的上调和下调。在复发时的临床样本中，其中4个基因（SP6、CCNE1、HIST1H2BH和DECR2）和2个基因（EVI2B和SYN1）也分别明显高于和低于诊断时的样本。结论大系列 BCP-ALL 细胞系是研究 BCP-ALL 白血病发病机制和疾病进展的有力研究工具。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

Utility of a Large Series of B-Cell Precursor Acute Lymphoblastic Leukemia Cell Lines as a Model System

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Utility of a Large Series of B-Cell Precursor Acute Lymphoblastic Leukemia Cell Lines as a Model System

Background

In B-cell precursor acute lymphoblastic leukemia (BCP-ALL), chromosomal translocations are strongly associated with prognoses. RNA sequencing (RNA-seq) is a powerful technology that reveals a close correlation between types of translocation and patterns of gene expression in clinical samples of BCP-ALL. Cancer cell lines are powerful research tools, and thus, we built a larger series of BCP-ALL cell lines and performed RNA-seq analysis to confirm their utility as a model system.

Methods

We performed RNA-seq in a total of 94 BCP-ALL cell lines, including 80 cell lines with 8 representative types of translocations.

Results

In the UMAP visualization, a close association was confirmed between the types of fusion genes and patterns of gene expression. In the cluster analysis of the gene expression profile, each type of fusion gene showed a clear association with the expression profile in the top 51 variable genes. Of clinical importance, the majority of the top variable genes in the BCP-ALL cell lines also showed a significant association with the types of fusion genes in the clinical samples. When an association of 125 cell cycle-related genes with the percentage of S and G2/M phases in 67 cell lines was evaluated, a significant positive correlation with cell cycle progression was confirmed in 10 cell cycle-related genes (HDAC2, CDC23, YWHAG, MAD2L1, CCNH, ANAPC7, CDC6, ANAPC5, ORC3, andRBX1). Moreover, significant upregulation and downregulation of 40 and 10 genes, respectively, were observed in the cell lines established at relapse compared with those established at diagnosis. Four (SP6, CCNE1, HIST1H2BH, and DECR2) and two (EVI2B and SYN1) of these genes were also significantly higher and lower, respectively, in the clinical samples at relapse than in those at diagnosis.

Conclusion

Large series of BCP-ALL cell lines is a powerful research tool for studying the mechanisms of leukemogenesis and the disease progression of BCP-ALL.

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来源期刊

Cancer Medicine ONCOLOGY-

CiteScore

5.50

自引率

2.50%

发文量

907

审稿时长

19 weeks

期刊介绍： Cancer Medicine is a peer-reviewed, open access, interdisciplinary journal providing rapid publication of research from global biomedical researchers across the cancer sciences. The journal will consider submissions from all oncologic specialties, including, but not limited to, the following areas: Clinical Cancer Research Translational research ∙ clinical trials ∙ chemotherapy ∙ radiation therapy ∙ surgical therapy ∙ clinical observations ∙ clinical guidelines ∙ genetic consultation ∙ ethical considerations Cancer Biology: Molecular biology ∙ cellular biology ∙ molecular genetics ∙ genomics ∙ immunology ∙ epigenetics ∙ metabolic studies ∙ proteomics ∙ cytopathology ∙ carcinogenesis ∙ drug discovery and delivery. Cancer Prevention: Behavioral science ∙ psychosocial studies ∙ screening ∙ nutrition ∙ epidemiology and prevention ∙ community outreach. Bioinformatics: Gene expressions profiles ∙ gene regulation networks ∙ genome bioinformatics ∙ pathwayanalysis ∙ prognostic biomarkers. Cancer Medicine publishes original research articles, systematic reviews, meta-analyses, and research methods papers, along with invited editorials and commentaries. Original research papers must report well-conducted research with conclusions supported by the data presented in the paper.