失调的miRNAs可作为星形细胞瘤的潜在治疗靶点:生物信息学分析
Dysregulated miRNAs as Potential Therapeutic Targets of Astrocytoma: Bioinformatics Analysis
DOI: 10.12677/acm.2024.1451611, PDF, HTML, XML, 下载: 58  浏览: 107 
作者: 苏 晶*, 刘国栋#:重庆医科大学附属第二医院神经外科,重庆;彭 路:苏州大学附属第一医院神经外科,江苏 苏州;巫 瑞:江油市人民医院神经外科,四川 绵阳
关键词: 星形细胞瘤胶质瘤微RNA生物标志物生物信息学Astrocytoma Glioma microRNAs Biomarker Bioinformatics
摘要: 目的:在神经系统常见肿瘤中,胶质瘤属于较难治疗的原发性肿瘤之一,一般具有预后较差、较高死亡率、常易复发等特点。其中,最常见的胶质瘤类型为星形细胞瘤,也是本次研究的目的。以当前的医疗水平,对胶质瘤尽早诊断和尽快进入规范化诊疗阶段是非常重要的,而从当前的治疗现状来看仍不尽人意。我们发现一种生物标志物——microRNAs (miRNAs),在上述疾病诊断及预后过程中存在巨大潜力,近期的多项研究表明它在星形细胞瘤的发生、发展、转归中都有研究价值。故本研究的主旨是探讨miRNA失调在星形细胞瘤发生发展中的重要性,并利用生物信息学分析以确定潜在的治疗靶点。方法:我们从GEO基因表达综合数据库(下称GEO)下载GSE138764和GSE132052两个经筛选后符合要求的微阵列数据集,并使用Rv3.6.2软件和KEGG通路分析对其进行分析。结果:综合生物分析结果,与星形细胞瘤发生、发展与转归呈重要相关的miRNAs或与以下靶点有关:细胞粘附因子、RNA聚合酶II、钙粘蛋白、泛素蛋白、转录辅助活化子、组蛋白、激素-受体结合体、肿瘤蛋白多糖、细胞衰老、以及多个信号通路(MAPK, PI3K-Akt, Hippo, mTOR)等。随即,我们从中选择10个在表达中差异最明显的miRNAs进行进一步研究:miR-138-2-3p、miR-377-5p、miR-517c-3p、miR-770-5p、miR-431-3p、miR-29b-2-5p、miR-433、miR-212-5p、miR-517a-3p、miR-490-3p,并发现,这些miRNA或与肿瘤细胞的增殖、迁移和侵袭等生理病理过程有关。结论:这些发现向我们揭示:星形细胞瘤的发生、发展及转归可能与miRNAs失调有关,NUPL2,miR-517c-3p和miR-431-3p等基因可能在进一步研究后证明对于星形细胞瘤具有重要的诊断价值,可以作为潜在的生物治疗靶点进行应用。
Abstract: Purpose: Glioma is one of the primary tumors that are difficult to treat in common nervous system tumors, which is generally characterized by poor prognosis, high mortality, and easy recurrence. Among them, the most common type of glioma is astrocytoma, which is also the purpose of this study. At the current level of medical treatment, early diagnosis and rapid entry into standardized diagnosis and treatment of gliomas are very important, but the current treatment status is still not satisfactory. We found that a biomarker, microRNAs (miRNAs), has great potential in the diagnosis and prognosis of the above-mentioned diseases. Many recent studies have shown that it has research value in the occurrence, development, and outcome of astrocytoma. Therefore, the main purpose of this study is to explore the importance of miRNA disorder in the occurrence and development of astrocytoma, and to use bioinformatics analysis to determine potential therapeutic targets. Methods: Two microarray datasets for GSE138764 and GSE132052 were downloaded from the Gene Expression Omnibus (GEO) database and analyzed with software Rv3.6.2, and KEGG Pathway Analysis. Results: The miRNAs implicated in astrocytoma were associated with the following targets: cell adhesion molecule, RNA polymerase II, ubiquitin protein, cadherin, transcription coactivator, histone, hormone receptor binding, proteoglycans in cancer, cellular senescence, MAPK signaling pathway, PI3K-Akt signaling pathway, Hippo signaling pathway, and mTOR signaling pathway. Next, we selected 10 miRNAs with the largest expression differences: miR-138-2-3p, miR-377-5p, miR-29b-2-5p, miR-517c-3p, miR-770-5p, miR-431-3p, miR-433, miR-212-5p, miR-517a-3p, miR-490-3p, and found that they were related to tumor cell proliferation, migration, and invasion. Conclusion: These findings suggest that dysregulated miRNAs are implicated in astrocytoma progression, and NUPL2, miR-517c-3p and miR-431-3p could be potential diagnosis biomarkers and therapeutic targets for astrocytoma.
文章引用:苏晶, 彭路, 巫瑞, 刘国栋. 失调的miRNAs可作为星形细胞瘤的潜在治疗靶点:生物信息学分析[J]. 临床医学进展, 2024, 14(5): 1729-1745. https://doi.org/10.12677/acm.2024.1451611

1. 简介

脑胶质瘤占原发性颅内恶性肿瘤的80%,其中星形细胞瘤是最常见的类型 ‎[1] 。根据其形态学特征,世界卫生组织将星形细胞瘤分为毛细胞性星形细胞瘤、弥漫性星形细胞瘤、间变性星形细胞瘤和多形性胶质母细胞瘤四个亚型 ‎[2] 。目前,胶质瘤的早期确诊和规范治疗还很难以令人满意,仍存在经过全切除或亚全切肿瘤,再加上积极放化疗等多种治疗后,星形细胞瘤患者的中位生存期仍在12~15个月左右 ‎[3] 。

最近的研究表明,microRNAs (miRNAs)在多种癌症的发生发展中扮演着重要角色 ‎[4] ‎[5] 。miRNAs可以调节包括细胞增殖、分化、迁移和凋亡在内的多种生物学过程 ‎[4] 。在神经系统疾病中,miRNAs被认为是阿尔茨海默病、帕金森病、脑缺血和颅内动脉瘤等神经系统疾病的诊断和预后生物标志物 ‎[6] ‎[7] ‎[8] ‎[9] 。

生物信息学分析已被应用于揭示潜在的疾病生物标志物,特别是基于对差异表达基因(DEGs)及其相关生物过程和潜在途径的分析。然而,miRNAs在星形细胞瘤中的作用仍不清楚。综合分析血液、脑组织或脑脊液中miRNAs表达异常是否可能是星形细胞瘤的生物标志物,有助于星形细胞瘤患者的早期诊断及提供更合适的治疗方案。因此,本研究旨在系统分析星形细胞瘤中miRNA表达异常的报道,并通过生物信息学分析揭示其潜在的治疗靶点。

2. 方法

2.1. 文献检索

根据PRISMA指南 ‎[10] ,从2010年1月到2023年1月,用关键词“miRNA”、“胶质瘤”、“星形细胞瘤”搜索EMBASE、Pub Med、Array Express和GEO。根据标题和摘要以及纳入和排除标准筛选合格的文献。检索到合格文献进行全文分析。文献检索和数据提取由两位研究人员独立完成。任何争议都将由第三位研究员解决。在Array Express和GEO以关键词“astrocytoma”搜索,根据MIAMET指南,从基因表达综合数据库(GEO)下载两个数据集GSE138764 (miRNA Profile)和GSE132052 (miRNA profile) (https://www.ncbi.nlm.nih.gov/geo/)。

2.2. 纳入标准

1) 病例对照研究,或前瞻性或回顾性队列研究;2) 定量测定血液或血液成分、脑脊液和脑组织中的miRNA水平;3) miRNA是星形细胞瘤的主要变量之一;4) 设对照组;5) 病人或动物模型;6) 样本量 > 5。

2.3. 排除标准

1) 无对照组;2) 星形细胞瘤不是变量;3) miRNA水平未被量化;4) 病例报告或综述文章;5) 全文不可用;6) 未提供分析结果。

2.4. 分析过程

2.4.1. 主成分分析

利用主成分分析(PCA)对临床过程或动物实验中获取的miRNA表达异常的数据集进行降维分析以了解样本间有无显著的特征差异。

2.4.2. miRNA在星形细胞瘤中的表达模式

使用基于方差的前500个miRNAs进行分层聚类分析以排除任何技术异常样本,并使用R-package limma对两个数据集进行差异表达分析。阈值设为p < 0.05,倍数变化 > 1.5或倍数变化 < 2/3。用非配对t检验分析标准化miRNA失调(上调或下调)。选取p < 0.05的miRNAs进行无监督层次聚类分析。然后,通过相关分析(Pearson相关,Bonferroni-Holm调整,a = 0.05)分析与星形细胞瘤相关的miRNAs表达模式。

2.4.3. 基因功能分析

对差异表达的miRNAs进行基因本体(GO)富集分析,p值<0.05为显著富集。进行了京都基因和基因组百科全书(KEGG)路径分析(http://www.genome.jp/kegg/)。

2.5. 免疫浸润分析

Tumor Immune Estimation Resource提供了对泛癌肿瘤免疫细胞的综合分析(cistrome.dfci.harvard.edu /TIMER/)。我们利用其访问了靶基因中的六种免疫浸润(B细胞、CD4+T细胞、CD8+T细胞、中性粒细胞、巨噬细胞和树突状细胞)。利用此网站提供的模块,包括生存和SCNA模块,用于探讨免疫细胞浸润和生存之间的关系。采用Kaplan-Meier生存曲线、log-rank检验和单因素Cox分析评价免疫相关基因特征和临床特征与总生存率的关系。协变量包括临床因素(年龄、性别、种族、肿瘤分期)和基因表达。SCNA模块提供了对给定基因不同体细胞拷贝数改变的肿瘤间肿瘤浸润水平的比较。

3. 结果

3.1. 纳入的研究

Table 1. Study design, sample size and related research results

表1. 研究设计、样本量和相关研究结果

在从Pub Med和EMBASE检索的966项研究中,对15项研究的全文进行了评估,9项研究被纳入数据提取(见表1)。从GEO中筛选出两个较为符合要求的基因集,其中GSE138764含有33个星形细胞肿瘤组织和9个非肿瘤人脑组织。患者的临床信息见表2。GSE132052含有4个小鼠星形细胞瘤组织和3个小鼠脑组织,分别取自出生后第60天小鼠的新皮质与出生后第60~150天小鼠的星形细胞瘤组织的肿瘤组织。

Table 2. Clinical characteristics of patients

表2. 患者的临床特征

3.2. 主成分分析

42例人类标本分为星形细胞瘤组和非肿瘤对照组。7只小鼠分为小鼠肿瘤组和小鼠对照组。我们分别对这两个数据集进行了主成分分析(见图1)。人类的胶质瘤样本的特征较为分散,没有明显的倾向,而非肿瘤样本的特征相较肿瘤组而言相对集中一些(见图1(A))。理想状态下,两个集会呈现完全分离的状态,代表两组样本差异明显,我们得出的结果虽然存在交叉,但考虑到数据集中包含大量的miRNA数据,相互之间可能存在影响,遂不能断定两组之间无明显差异,仍需进一步验证。而小鼠的肿瘤组及非肿瘤组则可看出相对明显的特征差异(见图1(B))。

(A) (B)

Figure 1. Principal component analysis; (A) Human samples: Astrocytoma samples were compared with non-tumor samples; (B) Mouse samples: Mice tumor samples were compared with normal tissues

图1. 主成分分析;(A) 人类样本:星形细胞瘤样本和非肿瘤样本相互对照;(B) 小鼠样本:小鼠肿瘤样本和正常组织相互对照

3.3. 差异miRNA的表达模式

(A) (B)

Figure 2. The heat maps display the expression pattern of differential expressed miRNAs. Blue represents low gene expression and red represents high gene expression; (A) The abscissa represents the 42 human samples, and the ordinate represents the 307 differential miRNAs; (B) The abscissa represents the 7 mouse samples, and the ordinate represents the 179 differential miRNAs

图2. 热图显示差异表达的miRNAs的表达模式。蓝色代表低基因表达,红色代表高基因表达;(A) 横坐标代表42个人类样本,纵坐标代表307个差异表达的miRNAs;(B) 横坐标代表7个小鼠样本,纵坐标代表179个不同的miRNA

差异miRNA的层次聚类显示,人星形细胞瘤和小鼠肿瘤组中miRNA的整体表达模式与对照组有很大差异(见图2)。在人星形细胞瘤组中,大多数miRNAs表达下调,而在无肿瘤对照组中,大多数miRNAs表达上调(见图2(A))。然而,小鼠样本显示出相反的结果(见图2(B))。小鼠肿瘤组多数miRNAs表达上调,对照组多数miRNAs表达下调。在人和小鼠标本中,肿瘤组的表达模式相似,而对照组的表达模式相似。这些结果显示,人和小鼠样本中的星形细胞瘤都与不同的miRNAs相关。此外,我们还选择了95个与星形细胞瘤相关的人miRNAs和179个小鼠miRNAs作进一步分析。

3.4. miRNA表达的相关性

(A) (B) (C) (D)

Figure 3. Correlation matrix within miRNAs cluster. (A) Astrocytic and non-tumor control miRNAs in non-tumor control group; (B) Astrocytic and non-tumor control miRNAs in astrocytic group; (C) Mouse tumor and Mouse control differential miRNA in Mouse control; (D) Mouse tumor and Mouse control differential miRNA in Mouse tumor. The color intensities (scale in the side bar) and the numbers indicate the degree of pairwise correlation

图3. miRNAs簇内相关矩阵。(A) 星形细胞瘤和非肿瘤样本的差异miRNA与非肿瘤对照组对照;(B) 星形细胞瘤和非肿瘤样本的差异miRNA与星形细胞瘤对照;(C) 小鼠肿瘤和小鼠正常组织的差异miRNA在小鼠正常组织中对照;(D) 小鼠肿瘤和小鼠正常组织的差异miRNA在小鼠肿瘤组织中对照。颜色强度(侧栏标度)和数字表明二者之间的相关性

人类95个miRNAs在星形细胞瘤中的表达大部分呈现强的正相关(见图3(A)和图3(B)),与它们表达模式的热图一致,并可能为之前的CPA主成分分析结果不显著提供解释(见图1(A))。此外,miRNA之间的表达相关性在小鼠样本中也很明显(见图3(C)和图3(D))。代表他们很可能共同参与星形细胞瘤的共同通路。

3.5. 验证miRNAs簇靶点

GO富集分析(见图4)和KEGG通路分析(见补充表)显示星形细胞瘤相关靶点包括细胞粘附分子、RNA聚合酶II、泛素蛋白、钙粘蛋白、转录辅激活因子、组蛋白、激素受体结合、癌中蛋白多糖、细胞衰老、MAPK信号通路,PI3K-Akt信号通路,Hippo信号通路,mTOR信号通路。这些靶点与肿瘤细胞的增殖、迁移和侵袭有关。为了确定调节这些途径的miRNAs并揭示新的潜在治疗靶点,我们选择了10个表达差异最大的miRNAs进行进一步分析(见表3)。

Table 3. Hypothesized targets and dysregulation of miRNA

表3. 失调的miRNA和其假设靶点

(A)(B)

Figure 4. GO enrichment analysis of astrocytic-non-tumor control differential expression miRNAs. BP indicates biological process, CC indicates cellular components, and MF indicates molecular function. The color indicates -log10 (p-value). Dot sizes represent genes count. (A) Human samples; (B) Mouse samples

图4. GO富集分析星形胶质细胞–非肿瘤对照差异表达miRNAs。BP表示生物学过程,CC表示细胞成分,MF表示分子功能。颜色表示-log10 (p值)。点大小代表基因计数。(A) 人类样本;(B) 小鼠样本

3.6. 免疫浸润验证结论

Figure 5. Kaplan-Meier survival curves comparing the high and low expression of NUPL2 in LGG and GBM

图5. NUPL2在LGG和GBM中的高、低表达的Kaplan-Meier存活曲线

并在经过pubmed和embase等文献库进行相关文献检索阅读后,排除其他目前已有相关免疫浸润研究的miRNA (见表3),筛选出目前暂无明确免疫浸润机制研究的基因,miR-517c-3p。筛选出miR-517c-3p的靶基因NUPL2并研究其对免疫系统的影响。通过生存分析,评估NUPL2的表达对胶质瘤预后是否有显著影响。Kaplan-Meier生存曲线表明,在低级别胶质瘤(LGG)中,高水平NUPL2患者的生存期明显短于低水平NUPL2患者,但在多形性胶质母细胞瘤(GBM)中,这一点并不明显(见图5)。接下来,我们通过免疫浸润分析发现免疫细胞浸润水平随着靶基因NUPL2的基因拷贝数的变化而变化。一些免疫细胞浸润水平似乎与NUPL2基因拷贝数的改变存在显著相关性,包括GBM中的B细胞、CD8+T细胞、巨噬细胞和树突状细胞;LGG中的B细胞、CD8+T细胞、CD4+T细胞、巨噬细胞、中性粒细胞和树突状细胞(见图6)。

Figure 6. Association between NUPL2 copy numbers and immune cell infiltration levels in GBM and LGG cohorts (*p < 0.05, **p < 0.01, ***p < 0.001)

图6. GBM和LGG队列中NUPL2拷贝数与免疫细胞浸润水平的关系(*p < 0.05, **p < 0.01, ***p < 0.001)

4. 讨论

星形细胞瘤是最常见侵袭性脑肿瘤,且现阶段星形细胞瘤的治疗效果不尽人意。然而,miRNAs现已引起了人们的重视,并逐渐开始发展以miRNA为基础的治疗方法。目前已有一些miRNA被证实与星形细胞瘤有关,比如有学者发现,miR-221在高级别胶质瘤中高表达,而miR-124在间变性星形细胞瘤中低表达。此外,miR-137的低表达与星形细胞瘤的临床晚期有关,而miR-181b的低表达或miR-21的高表达与星形细胞瘤患者的生存率低有关。因此,系统分析星形细胞瘤中的miRNAs对于更好地了解它们在星形细胞瘤中的作用具有重要意义。

在这项研究中,我们全面提取和分析了星形细胞瘤患者和动物模型中失调的miRNAs。此外,我们还进行了GO和KEGG通路分析,以探讨差异表达的miRNAs在星形细胞瘤发病机制中的潜在作用。结果提示,差异化的miRNAs可以调控肿瘤细胞的生长、增殖、迁移和侵袭,它们与星形细胞瘤的发生发展密切有关。

我们发现细胞粘附分子、RNA聚合酶II、组蛋白、泛素蛋白、钙粘蛋白、转录辅激活因子和激素受体的结合在GO分析中存在富集现象。这说明差异表达的miRNA可能通过调节上述物质来介导肿瘤的生长、增殖、迁移和侵袭 ‎[11] ‎[16] 。其中细胞粘附分子的调控与肿瘤的增殖密切相关。目前已有研究报道证实,突触粘附分子neuroligin-3 (NLGN3)通过PI3K-mTOR途径促进胶质瘤细胞增殖 ‎[12] 。而RNA聚合酶II的调控不仅影响着肿瘤细胞的转录和增殖,同时也影响着胶质细胞源性神经营养因子的转录。有研究者发现,高表达的Egr-1可能以非结合方式参与胶质细胞源性神经营养因子启动子II中RNA聚合酶II的募集,从而参与调节高级别胶质瘤细胞中的胶质细胞源性神经营养因子转录 ‎[12] 。组蛋白是真核生物细胞核中的碱性蛋白质,并作为DNA缠绕的线轴,在基因调控中发挥重要作用,且既往研究表明组蛋白乙酰转移酶KAT6A可以通过上调PI3K/AKT信号以促进细胞增殖 ‎[13] 。在泛素蛋白中,E3泛素蛋白连接酶2在胶质瘤中的异位表达增强了肿瘤细胞对凋亡的抵抗力 ‎[14] ,我们推测,失调的miRNA可能通过调控泛素蛋白来改变肿瘤细胞的凋亡,从而增加肿瘤细胞的增殖。同样也有学者发现,泛素蛋白连接酶E3C在胶质瘤细胞和组织中过度表达,并增加细胞迁移和侵袭 ‎[15] ,也证实了这一推测。钙粘蛋白是一种同亲型结合、Ca依赖的细胞粘着糖蛋白,其功能的表达或缺失可能与肿瘤的迁移和侵袭有关。研究表明,若Fyn相关激酶过度表达,可以增加N-钙粘蛋白的蛋白水平,从而抑制了胶质瘤细胞的侵袭和迁移 ‎[16] 。转录辅激活因子对胶质母细胞瘤的致瘤性至关重要 ‎[17] 。此外,膜孕酮、雄激素、甲状腺激素和促肾上腺皮质激素的激素受体在调节细胞增殖、迁移和侵袭方面也很重要 ‎[18] ‎[19] ‎[20] ‎[21] 。

KEGG通路分析表明,差异化的miRNAs参与了不同的信号转导途径,包括肿瘤蛋白多糖、MAPK信号转导途径、mTOR信号转导途径和hippo信号转导途径。根据现有的研究,我们推测上述途径与肿瘤细胞的增殖、凋亡、侵袭有关。蛋白多糖调节肿瘤微环境并在肿瘤细胞中驱动多种致癌途径 ‎[22] ‎[23] 。miRNA-499a通过抑制MAPK信号通路促进细胞凋亡,同时抑制胶质瘤细胞增殖 ‎[24] 。抑制Hippo途径转录辅激活因子YAP/TAZ抑制胶质母细胞瘤生长 ‎[25] 。miRNA-451通过靶向mTOR途径抑制胶质瘤细胞增殖和侵袭 ‎[26] 。此外,我们发现PI3K-Akt通路受小鼠标本中miRNAs的调控。据报道,胶质瘤的生长和侵袭受PI3K/AKT通路的调控 ‎[27] 。

为了更好地了解miRNAs在星形细胞瘤中的作用,我们重点研究了10个表达差异最大的miRNAs,研究表明其中8个miRNA都可能通过调节细胞增殖、凋亡、侵袭来促进星形细胞瘤的进展。高级别胶质瘤中的肿瘤细胞会释放出含有miR-770-5p、miR-433和miR-212-5p等miRNA的微泡 ‎[28] ‎[29] ‎[30] 。miR-433激活MAPK信号通路,通过靶向Rap1a抑制乳腺癌细胞生长 ‎[28] 。在神经系统中,miR-433在帕金森病中下调 ‎[29] 。此外,miR-433-3p通过靶向CREB抑制细胞生长 ‎[30] 。在乳腺癌中,miR-770-5p的过表达通过调节AKT和ERK抑制细胞侵袭和运动 ‎[31] 。miR-770-5p通过靶向糖尿病肾病中的TRIAP1调节足细胞凋亡 ‎[32] 。在急性髓系白血病患者和细胞系中,miR-212-5p通过靶向FZD5下调和调节细胞增殖和凋亡 ‎[33] 。miR-212-5p通过靶向Ptgs2 ‎[34] 提供抗铁致神经元死亡的保护。此外,miR-212-5p通过靶向TBX15 ‎[35] 抑制肾透明细胞癌细胞。迄今为止,miR-770-5p和miR-212-5p在星形细胞瘤中的作用尚未见报道。我们推测它们通过调节上述类似的靶点来促进星形细胞瘤的进展。

值得注意的是,miR-517c-3p和miR-431-3p尚未被报道与胶质瘤相关。在本研究中,我们确定了这两个miRNAs的靶基因。另外通过生存分析发现,高水平的NUPL2表达与星形细胞瘤患者的不良预后相关。这项研究的另一个重要方面是NUPL2与不同的免疫浸润水平相关。NUPL2在星形细胞瘤中的作用至今未见报道,但在泌尿系统肿瘤中,NUPL2可能是膀胱癌患者准确预测预后的一个有希望的模型 ‎[36] 。此外,通过公共数据库分析,我们观察了NUPL2与浸润性免疫细胞水平之间的相关性。确定NUPL2的特异性抑制如何影响肿瘤浸润性T细胞的功能和抗肿瘤活性是一个重要的研究领域。

5. 结论

据我们所知,这是首次对星形细胞瘤miRNAs数据库进行系统的生物信息学分析。我们的结果表明,失调的miRNAs与星形细胞瘤的临床变量相关,并参与星形细胞瘤细胞增殖、迁移和侵袭的调控。值得注意的是,靶基因NUPL2,和miR-431-3p可能成为星形细胞瘤潜在的诊断生物标志物和治疗靶点。然而,要了解miRNAs在星形细胞瘤中的作用并阐明其分子机制还需要进一步的研究。

附录

Table S1. Enrichment analysis of differentially expressed miRNAs in astrocytes and non-tumor controls by KEGG pathway (TOP15)

表S1. KEGG通路对星形细胞和非肿瘤对照差异表达miRNAs的富集分析(TOP15)

Table S2. Enrichment analysis of miRNAs differentially expressed by KEGG pathway in mouse tumor and mouse control (TOP15)

表S2. KEGG通路对小鼠肿瘤和小鼠对照差异表达miRNAs的富集分析(TOP15)

NOTES

*第一作者。

#通讯作者。

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