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白血病原始细胞中的基因表达比值可对急性髓系白血病的风险预测进行分层。

Repeat to gene expression ratios in leukemic blast cells can stratify risk prediction in acute myeloid leukemia.

机构信息

Max Planck Institute of Immunobiology and Epigenetics, Freiburg, Germany.

Novartis Institute for Biomedical Research (NIBR), Basel, Switzerland.

出版信息

BMC Med Genomics. 2021 Jun 26;14(1):166. doi: 10.1186/s12920-021-01003-z.

DOI:10.1186/s12920-021-01003-z
PMID:34174884
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8234671/
Abstract

BACKGROUND

Repeat elements constitute a large proportion of the human genome and recent evidence indicates that repeat element expression has functional roles in both physiological and pathological states. Specifically for cancer, transcription of endogenous retrotransposons is often suppressed to attenuate an anti-tumor immune response, whereas aberrant expression of heterochromatin-derived satellite RNA has been identified as a tumor driver. These insights demonstrate separate functions for the dysregulation of distinct repeat subclasses in either the attenuation or progression of human solid tumors. For hematopoietic malignancies, such as Acute Myeloid Leukemia (AML), only very few studies on the expression/dysregulation of repeat elements were done.

METHODS

To study the expression of repeat elements in AML, we performed total-RNA sequencing of healthy CD34 + cells and of leukemic blast cells from primary AML patient material. We also developed an integrative bioinformatic approach that can quantify the expression of repeat transcripts from all repeat subclasses (SINE/ALU, LINE, ERV and satellites) in relation to the expression of gene and other non-repeat transcripts (i.e. R/G ratio). This novel approach can be used as an instructive signature for repeat element expression and has been extended to the analysis of poly(A)-RNA sequencing datasets from Blueprint and TCGA consortia that together comprise 120 AML patient samples.

RESULTS

We identified that repeat element expression is generally down-regulated during hematopoietic differentiation and that relative changes in repeat to gene expression can stratify risk prediction of AML patients and correlate with overall survival probabilities. A high R/G ratio identifies AML patient subgroups with a favorable prognosis, whereas a low R/G ratio is prevalent in AML patient subgroups with a poor prognosis.

CONCLUSIONS

We developed an integrative bioinformatic approach that defines a general model for the analysis of repeat element dysregulation in physiological and pathological development. We find that changes in repeat to gene expression (i.e. R/G ratios) correlate with hematopoietic differentiation and can sub-stratify AML patients into low-risk and high-risk subgroups. Thus, the definition of a R/G ratio can serve as a valuable biomarker for AML and could also provide insights into differential patient response to epigenetic drug treatment.

摘要

背景

重复元件构成了人类基因组的很大一部分,最近的证据表明,重复元件的表达在生理和病理状态下都具有功能作用。具体来说,对于癌症,内源性逆转录转座子的转录通常受到抑制,以减弱抗肿瘤免疫反应,而异染色质衍生的卫星 RNA 的异常表达已被确定为肿瘤驱动因素。这些研究结果表明,不同重复亚类的失调在人类实体瘤的衰减或进展中具有不同的功能。对于血液系统恶性肿瘤,如急性髓系白血病 (AML),仅对重复元件的表达/失调进行了很少的研究。

方法

为了研究 AML 中重复元件的表达,我们对来自原发性 AML 患者标本的健康 CD34+细胞和白血病母细胞进行了总 RNA 测序。我们还开发了一种综合生物信息学方法,可以定量所有重复亚类(SINE/ALU、LINE、ERV 和卫星)的重复转录本的表达,以及相对于基因和其他非重复转录本(即 R/G 比)的表达。这种新方法可用作重复元件表达的指导特征,并已扩展到 Blueprint 和 TCGA 联盟的 poly(A)-RNA 测序数据集的分析中,这些数据集共包含 120 个 AML 患者样本。

结果

我们发现,重复元件的表达在造血分化过程中通常受到下调,并且重复元件与基因表达的相对变化可以对 AML 患者的风险预测进行分层,并与总生存概率相关。高 R/G 比可识别具有良好预后的 AML 患者亚组,而低 R/G 比则在具有不良预后的 AML 患者亚组中普遍存在。

结论

我们开发了一种综合生物信息学方法,该方法定义了一种用于分析生理和病理发育中重复元件失调的一般模型。我们发现,重复元件与基因表达的变化(即 R/G 比)与造血分化相关,并可将 AML 患者分为低风险和高风险亚组。因此,R/G 比的定义可以作为 AML 的有价值的生物标志物,并为患者对表观遗传药物治疗的不同反应提供见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3317/8234671/43cf26279099/12920_2021_1003_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3317/8234671/de5287bf61c6/12920_2021_1003_Fig1_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3317/8234671/7a203582c28a/12920_2021_1003_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3317/8234671/4f13141d7a2b/12920_2021_1003_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3317/8234671/43cf26279099/12920_2021_1003_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3317/8234671/de5287bf61c6/12920_2021_1003_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3317/8234671/70f2d17e7445/12920_2021_1003_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3317/8234671/9ca170b722e2/12920_2021_1003_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3317/8234671/21da0ac7ae59/12920_2021_1003_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3317/8234671/7a203582c28a/12920_2021_1003_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3317/8234671/4f13141d7a2b/12920_2021_1003_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3317/8234671/43cf26279099/12920_2021_1003_Fig7_HTML.jpg

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