通过miRNA基因表达谱的基因共表达网络构建对星形细胞瘤的基因靶标进行预测

星形细胞瘤为浸润性生长肿瘤,生长缓慢,多为隐形症状,难以早期发现。多数肿瘤切除后有复发可能,且复发后肿瘤可演变成间变性星形细胞瘤或多形性胶质母细胞瘤。因此寻找其生物标志物早期诊断,并研究新的治疗方法就十分重要。方法:通过选用GEO数据库的星形细胞瘤miRNA表达谱数据,进行差异分析以及靶基因预测,通过2者共表达网络的构建对筛选出的miRNA的研究价值进行探讨。结果:得出hsa-miR-29b-2-5p;hsa-miR-339-5p与hsa-miR-362-3p3个较为关键的miRNA及与3者关系密切的8个mRNA。结论:通过对8个mRNA在癌症中的作用的讨论,肯定了这3个关键miRNA作为潜在靶点的研究价值。     

磁共振波谱在星形细胞瘤恶性程度分级及癫痫的应用

星形细胞瘤是神经上皮源性肿瘤中最常见的一类肿瘤.占颅内肿瘤的17％,占神经上皮源性肿瘤的40％,肿瘤向周围”蟹足样”浸润性生长,且无包膜形成.磁共振波谱(magnetic resonance spectroscopy,MRS)是随着磁共振成像(magnetic resonance imaging,MRI)发展起来的唯一的一种无创性研究活体组织的代谢情况和生化指标的技术,目前已在中枢神经系统疾病的临床工作和科学研究中得到广泛应用.它能活体检测脑组织,提供关于神经元功能、细胞能量代谢、细胞膜增殖和崩解以及选择性神经递质活动等信息,为脑肿瘤的临床治疗和科学研究提供了一条新的途径.磁共振波谱在星形细胞瘤的肿瘤实质区及肿瘤周围区的代谢物比值有助于肿瘤分级诊断,并且MRS有助于判定肿瘤的浸润边界,指导临床术中立体定位及组织病理学检查.此外,代谢-解剖叠加伪彩图体现的肿瘤本身的异质性在高低级别肿瘤中也有差异.近年来,许多学者研究发现磁共振波谱在星形细胞瘤患者有无癫痫发作者的代谢物水平不同,二者间的相关研究需要进一步深入.     

综述与专论: 脊髓星形细胞瘤研究进展

脊髓星形细胞瘤是一种罕见的中枢神经系统恶性肿瘤,在流行病学、肿瘤临床学表型、分子遗传标记、治疗及研究方面有着独特特征。虽然随着手术技术的进步以及分子病理的发展,脑胶质瘤的研究和治疗取得较大进展,但脊髓星形细胞瘤的研究和治疗却发展缓慢。其原因一方面在于临床样本较少,难以开展研究,另一方面因其分子遗传独特性,对脑胶质瘤一线化疗药替莫唑胺敏感性差。因而亟需理清脊髓星形细胞瘤的研究现状,为改善其临床疗效梳理潜在方向。基于此,本文综述脊髓星形细胞瘤的临床特征、病理分型、分子遗传特征和当前治疗方法等方面的研究进展,在描绘脊髓星形细胞瘤的临床治疗现状和研究进展的基础上,提出了未来研究和治疗潜在方向。     

人脑星形细胞瘤中p53，Fas／FasL的表达及其与凋亡关系的研究

目的：探讨细胞凋亡在星形细胞瘤中的作用及其与p53、Fas和Fas配体（Fas ligand,FasL）的关系。方法：对43例星形细胞瘤的标本分别进行HE染色,TUNEL及免疫组化分别标记p53,Fas和FasL。结果：高级别肿瘤和低级别肿瘤间的凋亡无显著差异（P〉0．05）。高级别星形细胞瘤的p53,Fas和FasL的表达均显著高于低级别肿瘤（P均〈0．05）。结论：突变型p53可作为评价星形细胞瘤生物学行为的参考指标。与低级别星形细胞瘤相比,高级别肿瘤中的细胞凋亡受到了抑制,且Fas与FasL的过表达对细胞凋亡可产生明显影响。     

人脑星形细胞瘤中p53，Fas/FasL 的表达及其与凋亡关系的研究

目的:探讨细胞凋亡在星形细胞瘤中的作用及其与p53、Fas和Fas配体(Fas ligand,FasL)的关系。方法:对43例星形细胞瘤的标本分别进行HE染色,TUNEL及免疫组化分别标记p53,Fas和FasL。结果:高级别肿瘤和低级别肿瘤间的凋亡无显著差异(P>0.05)。高级别星形细胞瘤的p53,Fas和FasL的表达均显著高于低级别肿瘤(P均<0.05)。结论:突变型p53可作为评价星形细胞瘤生物学行为的参考指标。与低级别星形细胞瘤相比,高级别肿瘤中的细胞凋亡受到了抑制,且Fas与FasL的过表达对细胞凋亡可产生明显影响。     

RhoA在人脑星形细胞瘤中的表达及意义

目的:探讨RhoA在人脑星形细胞瘤中表达与肿瘤病理分级的关系.方法:免疫组化ABC法检测RhoA在80例人脑星形细胞瘤和10例正常脑组织标本中的表达并进行分析.结果:在正常脑组织中未见RhoA表达.RhoA在人脑星形细胞瘤的表达阳性率及免疫反应评分(IRS)分剐为56.25%、1.76±1.71.Ⅰ-Ⅳ级星形细胞瘤RhoA表达阳性率分别为35%(7/20)、45%(9/20)、65%(13/20)、80%(16/20).Ⅰ-Ⅳ级脑星形细胞瘤中RhoA IRS分别为0.78 1.05、1.12 1.04、2.15:1:1.59、3.31±2.14.结论:RhoA在人脑星形细胞瘤中高表达,且随着星形细胞瘤病理级别的增高而表达增强,RhoA在脑星形细胞瘤的发生过程中具有重要作用.     

利用TCGA数据库构建肾透明细胞癌相关miRNA预后模型

利用TCGA数据库中肾透明细胞癌的miRNA与mRNA数据及临床信息,构建由miRNA组成的预后风险评分模型,并筛选与生存预后相关的miRNA-mRNA调控关系对,为研究提供理论依据。下载并整理TCGA[JP+1]数据库中肾透明细胞癌的miRNA与mRNA数据;对数据进行差异分析,将差异表达的miRNA与临床信息进行合并,利用单因素与多因素Cox回归分析,构建预后模型并进行模型评价;对模型中的miRNA进行靶基因预测,结果与差异表达的mRNA进行取交集,构建miRNA-mRNA调控网络;对网络中的mRNA进行生存分析,筛选生存相关的miRNA-mRNA调控关系对。共得到49个差异表达的miRNA与3 613个差异表达的mRNA;预后模型计算公式为:风险值(risk score)=hsa-miR-21-5p表达量×0.603＋hsa-miR-1251-5p表达量×-0.093;调控网络中共纳入31个miRNA-mRNA调控关系对;对mRNA进行生存分析,共得到7个有价值的关系对。所构建预后模型可有效预测肾透明细胞癌患者生存预后情况,筛选到的miRNA-mRNA调控关系对可为相关研究与治疗提供参考。     

人脑星形细胞瘤中p27kip1蛋白和增殖细胞核抗原PCNA表达的变化

目的：研究p27kip1蛋白和增殖细胞核抗原（proliferating cell nuclear antigen, PCNA）在星形细胞瘤中的表达与肿瘤病理分级的关系,探讨p27kip1蛋白在星形细胞瘤演变过程中的意义。方法：SP免疫组化法对64例星形细胞瘤的p27kip1蛋白和PCNA表达进行观察。结臬：随着病理级别的升高,p27kip1阳性细胞百分率降低,而PCNA则相反,两者的表达成显著负相关。结论：p27kip1表达的缺失可能与星形细胞瘤的发生发展密切相关,PCNA能较客观地反映肿瘤的恶性程度。     

人脑星形细胞瘤中p27 kip1 蛋白和增殖细胞核抗原PCNA 表达的变化

目的:研究p27kip1蛋白和增殖细胞核抗原(proliferating cell nuclear antigen,PCNA)在星形细胞瘤中的表达与肿瘤病理分级的关系,探讨p27kip1蛋白在星形细胞瘤演变过程中的意义。方法:SP免疫组化法对64例星形细胞瘤的p27kip1蛋白和PCNA表达进行观察。结果:随着病理级别的升高,p27kip1阳性细胞百分率降低,而PCNA则相反,两者的表达成显著负相关。结论:p27kip1表达的缺失可能与星形细胞瘤的发生发展密切相关,PCNA能较客观地反映肿瘤的恶性程度。     

三阴性乳腺癌相关miRNA筛选及其靶基因的生物信息学分析

应用生物信息学方法筛选并分析三阴性乳腺癌（triple-negative breast cancer,TNBC）相关miRNA及其靶基因,为TNBC的研究提供潜在的分子靶点。采用GEO2R分析TNBC相关miRNA芯片数据集,筛选差异表达倍数最大的5个上调和5个下调miRNA。miRWalk、TargetScan和miRDB预测靶基因并进行Veen分析取交集。利用DAVID对靶基因进行GO富集分析和KEGG通路分析。利用STRING数据库构建蛋白互作网络,并结合Cytoscape构建miRNA-靶基因调控网络,从而筛选出关键的miRNA及其关键靶基因。利用GEPIA2数据库对靶基因进行生存分析。GEO2R筛选出486个差异miRNA,上调和下调的miRNA分别有298个和188个。对差异倍数最大的5个上调和5个下调miRNA的靶基因进行富集分析显示,靶基因主要参与ErbB信号通路、癌症中转录调控紊乱和cGMP-PKG信号通路等。miRNA-靶基因调控网络显示,表达上调的关键miRNA为miR-611,其关键靶基因为CDC27、UBE2D2、UBR1、SPSB1、HERC2和RLIM;表达下调的关键miRNA为miR-1205,其关键靶基因为WSB1、FBXL8、UBE2W、PTPN11、ARF6、DNAJC6和COPS2。生存分析表明,UBR1（P=0.007 2）和PTPN11（P=0.029）表达上调可显著降低TNBC患者的整体生存率。经筛选获得的关键miRNA及其关键靶基因可作为潜在分子标记物用于TNBC的早期诊断、治疗靶点选择和预后判断,并为后续的研究提供参考依据。     

结节性甲状腺肿circRNA-miRNA-mRNA调控网络的构建

基于生物信息分析筛选结节性甲状腺肿中差异表达的环状RNA(circRNA),并揭示circRNA-miRNA-mRNA调控网络在结节性甲状腺肿中的作用。从GEO数据库中检索结节性甲状腺肿组织基因芯片数据,利用R软件筛选出差异表达的circRNA。联合多个生物信息数据库预测差异表达circRNA下游的miRNA及mRNA, 并对靶mRNA进行GO及KEGG富集分析。利用STRING在线数据库及Cytoscape软件筛选核心基因。确定了2个circRNA,42个miRNA及546个mRNA。GO及KEGG富集分析表明靶mRNA主要涉及细胞生长及基因表达调控过程。基于Cytoscape软件筛选出了14个核心基因(SP1、IGF1R、RPS6KB1、SMAD2、SMAD3、SMAD4、VEGFA、CCND1、CDK2、HSPA4、HIF1A、CREB1,NR3C1和STAT5A)。最终基于2个circRNA、11个miRNA和14个核心mRNA构建了circRNA-miRNA-mRNA调控网络。结节性甲状腺肿组织中异常表达的circRNA及相关的circRNA-miRNA-mRNA调控网络可能成为结节性甲状腺肿诊断与治疗的新靶点。     

Development and validation of a novel epigenetic signature for predicting prognosis in colon cancer

Epigenetic factors play a critical role in carcinogenesis by imparting a distinct feature to the chromatin architecture. The present study aimed to develop a novel epigenetic signature for evaluating the relapse-free survival of colon cancer patients. Public microarray datasets were acquired from the Gene Expression Omnibus databases: GSE39582, GSE17538, GSE33113, and GSE37892 set. Patients from GSE39582 set were randomized 1:1 into training and internal validation series. Patients were divided into high-risk and low-risk groups in training series based on a set of 11 epigenetic factors (p < .001). The good reproducibility for the prognostic value of the epigenetic signature was confirmed in the internal validation series (p < .001), external validation series (a combination of GSE17538 set, GSE33113 set, and GSE37892 set; p = .018), and entire series (p < .001). Furthermore, a nomogram, which integrated the epigenetic signature, pathological stage, and postoperative chemotherapy, was developed based on the GSE39582 set. The time-dependent receiver operating characteristic curve at 1 year demonstrated that the comprehensive signature presented superior prognostic value than the pathological stage. In conclusion, an epigenetic signature, which could be utilized to divide colon cancer patients into two groups with significantly different risk of relapse, was established. This biomarker would aid in identifying patients who require an intensive follow-up and aggressive therapeutic intervention.     

Common miRNAs,candidate genes and their interaction network across four subtypes of epithelial ovarian cancer

Epithelial ovarian cancer (EOC) is categorized into four major histological subtypes such as clear cell carcinoma (CCC), endometrioid carcinoma (EC), mucinous carcinoma (MC), and serous carcinoma (SC). Heterogeneity of the EOC leads to different clinical outcomes of the disease, although all the subtypes are originated from the same layer of tissue. Therefore, it is of interest to identify the common candidate genes, miRNA and their interaction network in four the subtypes of EOC. A comparative gene expression analysis identified 248 common differentially expressed genes (DEGs) in the four subtypes of EOC. Identified common DEGs were found to be enriched in cancer specific pathways. A protein-protein interaction (PPI) network of the common DEGs were constructed, and subsequent module and survival analyses identified seven key candidate genes (CCNB1, CENPM, CEP55, RACGAP1, TPX2, UBE2C, and ZWINT). We also documented 10 key candidate miRNAs (hsa-mir-16-5p, hsa-mir-23b-3p, hsa-mir-34a-5p, hsa-mir-103a-3p, hsa-mir-107, hsa-mir-124-3p, hsa-mir-129-2-3p, hsa-mir-147a, hsa-mir-205-5p, and hsa-mir-195-5p) linked to the candidate genes. These derived data find application in the understanding of EOC.     

An EMT‐related gene signature for the prognosis of human bladder cancer

The transition from non–muscle‐invasive bladder cancer (NMIBC) to muscle‐invasive bladder cancer (MIBC) is detrimental to bladder cancer (BLCA) patients. Here, we aimed to study the underlying mechanism of the subtype transition. Gene set variation analysis (GSVA) revealed the epithelial‐mesenchymal transition (EMT) signalling pathway with the most positive correlation in this transition. Then, we built a LASSO Cox regression model of an EMT‐related gene signature in BLCA. The patients with high risk scores had significantly worse overall survival (OS) and disease‐free survival (DFS) than those with low risk scores. The EMT‐related gene signature also performed favourably in the accuracy of prognosis and in the subtype survival analysis. Univariate and multivariate Cox regression analyses demonstrated that the EMT‐related gene signature, pathological N stage and age were independent prognostic factors for predicting survival in BLCA patients. Furthermore, the predictive nomogram model was able to effectively predict the outcome of BLCA patients by appropriately stratifying the risk score. In conclusion, we developed a novel EMT‐related gene signature that has tumour‐promoting effects, acts as a negative independent prognostic factor and might facilitate personalized counselling and treatment in BLCA.