Competing endogenous RNA networks related to prognosis in chronic lymphocytic leukemia: comprehensive analyses and construction of a novel risk score model.

Competing endogenous RNA networks related to prognosis in chronic lymphocytic leukemia: comprehensive analyses and construction of a novel risk score model.
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与慢性淋巴细胞性白血病预后相关的竞争性内源性RNA网络:全面的分析和建立新的风险评分模型。

DOI:
10.1186/s40364-022-00423-y
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发表时间:
2022-10-21
期刊:
影响因子:
11.1
通讯作者:
--
中科院分区:
医学2区
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--
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慢性淋巴细胞白血病(CLL)是一种异质性的b细胞恶性肿瘤,缺乏特异性的生物标志物和药物靶点。竞争内源性rna (ceRNAs)通过海绵microRNAs (miRNAs)在肿瘤发生和肿瘤进展中发挥重要作用。然而,CLL中与生存相关的ceRNA网络的调控机制仍有待发现。我们纳入了865名新生CLL患者来研究RNA表达谱,并对我们中心的4名CLL患者、2株CLL细胞系和6名健康供者进行了Illumina测序。通过单因素Cox回归、LASSO回归和多因素Cox回归分析,建立了CLL患者风险评分新模型。用CIBERSORT和ESTIMATE程序比较低危组和高危组的免疫特征。随后,我们分析了差异表达miRNAs (DEmiRNAs)与IGHV突变状态、p53突变状态和del17p之间的关系。基于生存分析和具有靶向关系的差异表达rna,构建lncRNA/circRNA-miRNA-mRNA ceRNA网络。此外,我们对circRNA circ_0002078/miR-185-3p/TCF7L1轴进行了验证,并通过双荧光素酶报告基因测定描绘了它们之间的相互关系。在CLL患者标本与正常B细胞之间共鉴定出57种差异表达mrna (demrna)和335种差异表达mrna。建立并验证了HTN3、IL3RA和NCK1组成的新型风险评分模型。模型在训练集、检验集和总集上的一致性指数分别为0.825、0.719和0.773。高危组与del(13q14)以及较短的总生存期(OS)相关。此外,我们还发现了与CLL患者细胞遗传学异常相关的DEmiRNAs,发现miR-324-3p与IGHV突变、p53突变和del17p相关。构建了与生存相关的lncRNA/circRNA-miRNA-mRNA ceRNA网络,以进一步促进潜在预测生物标志物的开发。此外,circ_0002078和TCF7L1的表达在CLL患者中显著升高,miR-185-3p的表达明显降低。Circ_0002078通过与TCF7L1竞争miR-185-3p来调节TCF7L1的表达。RNA表达谱的综合分析为CLL的分子机制提供了开创性的见解。新的风险评分模型和与生存相关的ceRNA网络促进了CLL预后生物标志物和潜在治疗脆弱性的发展。在线版本包含补充材料,可在10.1186/s40364-022-00423-y获得。
Chronic lymphocytic leukemia (CLL) is a heterogeneous B-cell malignancy that lacks specific biomarkers and drug targets. Competing endogenous RNAs (ceRNAs) play vital roles in oncogenesis and tumor progression by sponging microRNAs (miRNAs). Nevertheless, the regulatory mechanisms of survival-related ceRNA networks in CLL remain to be uncovered. We included 865 de novo CLL patients to investigate RNA expression profiles and Illumina sequencing was performed on four CLL patients, two CLL cell lines and six healthy donors in our center. According to univariate Cox regression, LASSO regression as well as multivariate Cox regression analyses, we established a novel risk score model in CLL patients. Immune signatures were compared between the low- and high-risk groups with CIBERSORT and ESTIMATE program. Afterwards, we analyzed the relationship between differentially expressed miRNAs (DEmiRNAs) and IGHV mutational status, p53 mutation status and del17p. Based on the survival analyses and differentially expressed RNAs with targeting relationships, the lncRNA/circRNA-miRNA-mRNA ceRNA networks were constructed. In addition, the circRNA circ_0002078/miR-185-3p/TCF7L1 axis was verified and their interrelations were delineated by dual-luciferase reporter gene assay. Totally, 57 differentially expressed mRNAs (DEmRNAs) and 335 DEmiRNAs were identified between CLL patient specimens and normal B cells. A novel risk score model consisting of HTN3, IL3RA and NCK1 was established and validated. The concordance indexes of the model were 0.825, 0.719 and 0.773 in the training, test and total sets, respectively. The high-risk group was related to del(13q14) as well as shorter overall survival (OS). Moreover, we identified DEmiRNAs that related to cytogenetic abnormality of CLL patients, which revealed that miR-324-3p was associated with IGHV mutation, p53 mutation and del17p. The survival-related lncRNA/circRNA-miRNA-mRNA ceRNA networks were constructed to further facilitate the development of potential predictive biomarkers. Besides, the expression of circ_0002078 and TCF7L1 were significantly elevated and miR-185-3p was obviously decreased in CLL patients. Circ_0002078 regulated TCF7L1 expression by competing with TCF7L1 for miR-185-3p. The comprehensive analyses of RNA expression profiles provide pioneering insights into the molecular mechanisms of CLL. The novel risk score model and survival-related ceRNA networks promote the development of prognostic biomarkers and potential therapeutic vulnerabilities for CLL. The online version contains supplementary material available at 10.1186/s40364-022-00423-y.
DOI: 10.1186/s40364-021-00317-5
发表时间: 2021-08-23
期刊: Biomarker research
影响因子: 11.1
作者:
Flowers E;Allen IE;Kanaya AM;Aouizerat BE
通讯作者: Aouizerat BE
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发表时间: 2021-05-17
影响因子: 12.8
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影响因子: --
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通讯作者: Zhang Y
DOI: 10.3390/cancers13030437
发表时间: 2021-01-24
期刊: Cancers
影响因子: 5.2
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发表时间: 2013-10
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影响因子: 28.2
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通讯作者: Pandolfi PP