高分级胶质瘤的放疗

脑胶质瘤的分类,一是kernohan按恶性度分类,数字分级表示。恶性度最低为星形细胞瘤Ⅰ级,神经胶质母细胞瘤和有分化差倾向的显形细胞瘤为Ⅱ级,星形细胞瘤Ⅲ和Ⅳ级为有低、高度恶性的多形性胶质母细胞瘤。也有作者只将星形细胞瘤Ⅳ级归为多形性胶质母细胞瘤。     

高分级胶质瘤的放化综合治疗

胶质瘤是起源于神经胶质细胞的肿瘤，主要包括星形细胞肿瘤、少突胶质细胞肿瘤和混合性胶质细胞肿瘤。星形细胞瘤是胶质瘤中最常见的类型，其中的间变性星形细胞瘤又称恶性星形细胞瘤，属WHOⅢ级。临床常将恶性星形细胞瘤和胶质母细胞瘤统称为恶性胶质瘤，而将Ⅲ级胶质瘤（如间变性星形细胞瘤，间变性少突胶质细胞瘤）、胶质母细胞瘤、胶质肉瘤等统称为高分级胶质瘤。     

胶质母细胞瘤的分子生物学研究进展

摘 要：胶质母细胞瘤是最常见、恶性程度最高的浸润性脑胶质瘤,具有形态学、遗传学和基因表达异质性,目前标准的治疗方法是最大程度的手术切除并辅以放疗和化疗。由于异质性的存在,大多数肿瘤会对治疗产生抗性并在短时间内复发。随着遗传分子学的研究进展对胶质母细胞瘤的分类以及病理生理学有了更多的理解。全文对胶质母细胞瘤的组织病理学分类、分子分类、病理生理学、临床相关的遗传分子的改变以及可能的发病机制进行综述。     

胶质瘤中MKK7与c-Jun磷酸化的表达及其相关性

目的 探讨胶质瘤中MKK7和c-Jun磷酸化（p-c-Jun）的表达及意义，分析两者表达的相关性。方法 选取弥漫型星形细胞瘤（15例）、少突胶质细胞瘤（5例）、间变性星形细胞瘤（11例）、间变性少突胶质细胞瘤（8例）、胶质母细胞瘤（53例）及其瘤旁正常脑组织（25例）共117例，采用免疫组织化学法检测MKK7、c-Jun及p-c-Jun的表达。体外培养神经胶质瘤细胞株U87，用脂质体转染MKK4-siRNA、MKK7-siRNA和对照siRNA，48 h后Western blot检测MKK7、c-Jun及p-c-Jun的表达水平。结果 胶质母细胞瘤中p-c-Jun及MKK7的表达均明显高于其他组织学类型胶质瘤及胶质母细胞瘤瘤旁正常脑组织中的表达（P=0.000, P=0.000）。随着胶质瘤WHO分级的升高，p-c-Jun及MKK7的表达增高，且与WHO分级呈明显正相关（r=0.494, P=0.000; r=0.606, P=0.000）。胶质瘤及胶质母细胞瘤瘤旁正常脑组织中MKK7与p-c-Jun的表达存在正相关关系（r=0.387, P=0.000）。沉默神经胶质瘤细胞株U87 MKK7表达抑制了c-Jun磷酸化水平。结论 MKK7可以通过调控JNK/c-Jun活性进而促进胶质母细胞瘤的发生。     

胶质瘤位点特异性分布的相关因素探讨

神经胶质瘤是中枢神经系统肿瘤中最为常见的恶性肿瘤,其治疗极具挑战性。胶质母细胞瘤属于WHOⅣ级的高度恶性脑胶质瘤,常规治疗包括手术、术后化疗联合放疗,然而由于它的高度浸润性、遗传异质性和血脑屏障的存在为胶质母细胞瘤的治疗带来了艰巨的任务,几乎所有胶质母细胞瘤在积极治疗后都会复发,提高胶质瘤总体治疗效率促使我们探索更新的分子治疗策略。大脑的解剖和功能区定义是现代神经外科学的重要理念,是研究脑胶质瘤分布差异的基础。本文从胶质瘤的起源出发,基于大脑连接组学研究的理论,从分子特征、信息通路、肿瘤微环境景观、免疫等方面分析了胶质瘤空间特异分布的可能原因,试图寻找新的生物分子靶标治疗路径,为胶质瘤更有效的治疗提供一些新的科学思路。     

星形细胞瘤临床病理研究

目的对星形细胞瘤进行分级，探讨组织类型、分级与复发、预后的关系。方法依据WHO神经系统肿瘤新分类对79例颅内星形细胞瘤的临床和病理资料进行回顾性研究。结果组织类型、分级与预后生存率差异有显著性，Ⅲ级间变性星形细胞瘤和Ⅳ级胶质母细胞瘤术后2年、5年的生存率偏低。结论星形细胞瘤患者的预后与病理组织学类型、分级明显相关。     

脑肿瘤新分类及其生物学进展

世界卫生组织于１９７９年首次进行了中枢神经系统肿瘤的组织学分类，１０年来，由于肿瘤生物学的发展，极大丰富了对脑肿瘤的认识，１９９０年ＷＨＯ邀请了美，英，德，日等１１个国家的著名专家，重新分类脑肿瘤，增加了多型性黄色星形细胞瘤，神经细胞瘤，纤维形成性婴儿神经节细胞胶质瘤和胚发育不良性神经上皮瘤，胶质母细胞瘤又新归为星形细胞瘤范畴，同时对儿童脑肿瘤作了详细分类，在形态学和分子生物学基础上论述了脑肿瘤的     

Rb2/p130、CyclinD1在脑胶质瘤中的表达及意义

[目的]观察Rb2/p130、CyclinD1在脑胶质细胞瘤中的表达及其相关性,并探讨其与脑胶质细胞瘤临床病理分级的关系。[方法]选取Ⅰ~Ⅳ级脑胶质细胞瘤80例,并对其蜡块进行免疫组化SP法染色,检测Rb2/p130、CyclinD1在脑胶质细胞瘤中的表达。[结果]本组80例脑胶质细胞瘤中44例有不同程度的CyclinD1表达,阳性率为55.0%（44/80）。不同病理分级的脑胶质细胞瘤中CyclinD1的表达有统计学差异。随胶质瘤的恶性度增高,表达率上升。p130的阳性率为71.3%（57/80）,在不同病理分级的胶质瘤中,CyclinD1表达存在统计学差异,即随胶质瘤病理分级的增高,p130的表达率降低。CyclinD1与p130表达呈负相关。[结论]CyclinD1随脑胶质细胞瘤级别的增高,其阳性表达逐渐增强,而Rb2/p130则相反。CyclinD1的正调控与Rb2/p130的负调控可能是影响脑胶质细胞瘤发生发展的重要因素。     

神经胶质瘤的治疗研究进展

<正>神经胶质瘤是来源于神经上皮的肿瘤,占全部颅内肿痛的40%～50%,中低度分化星形细胞瘤和胶质母细胞瘤患者的1年存活率小于5%,具有高发病率、高复发率、高病死率和低治愈率的特点。根据胶质瘤细胞的分化情况又分为:星形细胞瘤、少突胶质瘤、室管膜瘤、髓母细胞瘤、多形性胶质母细胞瘤等,由于其分化差、增殖快、侵袭     

胶质母细胞瘤诊疗研究进展

胶质母细胞瘤是最常见的原发性颅内恶性肿瘤。尽管在过去的几十年里进行了大量的研究,胶质母细胞瘤的预后仍然很差。近年来随着多组学等研究在胶质母细胞瘤中的应用,加深了人们对胶质母细胞瘤的认识,主要体现在诊断上对其分类进行了重新修订。治疗上,在原有的手术和放化疗等标准治疗基础上发展了靶向治疗、免疫治疗和电场治疗等新型治疗方法。本文对胶质母细胞瘤近年来在诊疗中取得的最新进展进行简要述评。     

Application of advances in molecular biology to the treatment of brain tumors

Recent advances in molecular biology have substantially improved our understanding of the molecular genetics of primary brain neoplasms. Soon each histopathologic category of glioma will be further divided into subgroups according to similar genetic background, gene expression profile, and similarity of biologic responses to radiotherapy or chemotherapy. Identification of key molecules that are specifically altered in neoplastic cells will provide candidate molecular targets for tumor treatment. Novel therapeutic tools for targeting tumor cells, such as viral vectors for gene therapy, have been created. In the near future, the accumulation of new knowledge in brain tumor biology and genetics, combined with rational drug design, will revolutionize the treatment of malignant gliomas, which are among the most lethal human cancers.     

Molecular voting for glioma classification reflecting heterogeneity in the continuum of cancer progression

Gliomas, the most common brain tumors, are generally categorized into two lineages (astrocytic and oligodendrocytic) and further classified as low-grade (astrocytoma and oligodendroglioma), mid-grade (anaplastic astrocytoma and anaplastic oligodendroglioma), and high-grade (glioblastoma multiforme) based on morphological features. A strict classification scheme has limitations because a specific glioma can be at any stage of the continuum of cancer progression and may contain mixed features. Thus, a more comprehensive classification based on molecular signatures may reflect the biological nature of specific tumors more accurately. In this study, we used microarray technology to profile the gene expression of 49 human brain tumors and applied the k-nearest neighbor algorithm for classification. We first trained the classification gene set with 19 of the most typical glioma cases and selected a set of genes that provide the lowest cross-validation classification error with k=5. We then applied this gene set to the 30 remaining cases, including several that do not belong to gliomas such as atypical meningioma. The results showed that not only does the algorithm correctly classify most of the gliomas, but the detailed voting results also provide more subtle information regarding the molecular similarities to neighboring classes. For atypical meningioma, the voting was equally split among the four classes, indicating a difficulty in placement of meningioma into the four classes of gliomas. Thus, the actual voting results, which are typically used only to decide the winning class label in k-nearest neighbor algorithms, provide a useful method for gaining deeper insight into the stage of a tumor in the continuum of cancer development.     

基于GINS家族成员在胶质瘤组织中的表达水平对其进行分型及其临床意义

目的：基于GINS家族成员在胶质瘤组织中表达水平对其分型,探究此分型预测胶质瘤患者的预后、免疫治疗疗效的有效性,采用TCMOI数据库虚拟筛选可靶向GINS的中药小分子。方法：数据库分析GINS基因组学、胶质瘤组织中差异表达基因与患者预后的关系,基于GINS家族成员基因表达对胶质瘤进行分型并分析各亚型的预后情况,数据库数据分析各亚型中的基因突变、基因富集、肿瘤纯度和免疫细胞浸润评分,以及与GINS2可能相互作用的中药小分子,最后用qPCR法检测中国人胶质瘤组织中GINS1～4 mRNA的表达水平以验证其与数据库数据的一致性。结果：GINS家族各成员间的基因、蛋白结构和功能相似,胶质瘤组织中GINS家族成员呈高表达且与患者不良预后密切相关（P<0.05）,基于GINS家族成员在胶质瘤组织中表达水平的S1、S2亚型分类能较好地预测胶质瘤患者的预后,S1亚型主要突变基因为CDKN2A/B、EGFR、PTEN而S2亚型的突变基因为IDH1、TP53和ATRX,GINS家族可能通过调控免疫微环境影响胶质瘤患者预后,CD276和CX3CL1可能是S1亚型胶质瘤患者实施免疫治疗的潜在靶点,CHE...     

胶质瘤细胞诱导分化相关基因在胶质瘤组织中的表达

目的 利用已经建立的胶质瘤细胞诱导分化相关基因表达谱，筛选胶质瘤恶性进展相关基因。方法 按分子生物学实验要求，收集经病理确诊的不同恶性程度胶质瘤手术标本，应用反向多点杂交技术制作分子探针，与96个相关基因组成的小芯片杂交检测在不同恶性级别胶质瘤手术标本中的表达情况。结果共有8个基因在各个恶性级别胶质瘤中均呈高表达；有14个基因随胶质瘤恶性程度升高而表达频率呈上升趋势；有6个基因随胶质瘤恶性程度升高表达频率呈下降趋势；筛选到可能与胶质瘤恶性进展有关的新基因有DIP1、RPS7、CLK2、WWOX／FOR、GRIM-19等基因。结论 本研究制作的胶质瘤细胞分化相关基因小芯片，在不同级别胶质瘤组织标本中检测到的表达情况，可进一步用于胶质瘤恶性进展的分子机制研究。     

Comprehensive analysis of microRNA expression profile in malignant glioma tissues

Malignant gliomas represent the most devastating group of brain tumors in adults, among which glioblastoma multiforme (GBM) exhibits the highest malignancy rate. Despite combined modality treatment, GBM recurs and is invariably fatal. A further insight into the molecular background of gliomagenesis is required to improve patient outcomes. The primary aim of this study was to gain broad information on the miRNA expression pattern in malignant gliomas, mainly GBM. We investigated the global miRNA profile of malignant glioma tissues with miRNA microarrays, deep sequencing and meta‐analysis. We selected miRNAs that were most frequently deregulated in glioblastoma tissues, as well as in peritumoral areas, in comparison with normal human brain. We identified candidate miRNAs associated with the progression from glioma grade III to glioma grade IV. The meta‐analysis of miRNA profiling studies in GBM tissues summarizes the past and recent advances in the investigation of the miRNA signature in GBM versus noncancerous human brain and provides a comprehensive overview. We propose a list of 35 miRNAs whose expression is most frequently deregulated in GBM patients and of 30 miRNA candidates recognized as novel GBM biomarkers.     

Cluster Analysis and Significance of Novel Genes Related to Molecular Classification of Glioma

Objective To screen differentially expressed genes in the development of human glioma and establish a primary molecular classification of glioma based on gene expression using cDNA microarrays. Methods Brain specimens were obtained from 18 patients with glioma, 10 males and 8 females, ages 14–62 with an average age of 44.4. The total RNAs of these glioma specimens and two specimens of donated brain of normal adults were extracted. BioStarH140S microarrays (including 8,347 old genes and 5,592 novel genes) were adopted and hybridized with probes which were prepared from the total RNAs. Differentially expressed genes between normal tissues and glioma tissues were assayed after scanning cDNA microarrays with ScanArray4000. Northern hybridization and in situ hybridization (ISH) were used to identify functions of novel genes. Those differentially expressed genes were studied with a Hierarchical method and molecular classification of glioma was preliminary carried out. Results Among the 13,939 target genes, there were 1,200 (8.61% ) differentially expressed genes, of which 395 (2.83%) were novel genes. A total of 348 genes were up—regulated and 852 genes were down—regulated in the gliomas. The results of bioinformatical analysis, Northern hybridization and ISH revealed that those novel genes were highly associated with gliomas. There were multiple genes, such as the MAP gene cytoskeleton & matrix motility genes, etc, which were of relevance to classification by the Hierarchical method. Molecular classification of glioma using a Hierarchical cluster was in accordance with pathology and suggested a molecular process of tumorigenesis and development. Conclusion Multiple genes play important roles in development of glioma. cDNA microarray technology is a powerful technique in screening for differentially expressed genes between two different kinds of tissues. Further analysis of gene expression and novel genes would be helpful to understand the molecular mechanism of glioma development. This work was supported by the National Natural Science Foundation (30471777) and the Natural Science Foundation of Shanghai (034119835).     

弥漫大B细胞淋巴瘤的分类及预后研究进展

弥漫大B细胞淋巴瘤（DLBCL）在临床表现、病理形态和遗传学特征方面具有高度异质性。从形态学角度,2008年WHO分类将DLBCL定义为弥漫生长的大B细胞淋巴瘤,其细胞核等大或大于正常巨噬细胞核。近几年,研究着重于将临床特征、形态学、免疫组织化学甚至基因表达谱融合到DLBCL的分类中,通过基因表达谱来对DLBCL进行分类。文章从DLBCL基因表达谱分类、免疫组织化学分型及其对预后的作用等方面进行综述。     

Gene expression-based molecular diagnostic system for malignant gliomas is superior to histological diagnosis.

PURPOSE: Current morphology-based glioma classification methods do not adequately reflect the complex biology of gliomas, thus limiting their prognostic ability. In this study, we focused on anaplastic oligodendroglioma and glioblastoma, which typically follow distinct clinical courses. Our goal was to construct a clinically useful molecular diagnostic system based on gene expression profiling. EXPERIMENTAL DESIGN: The expression of 3,456 genes in 32 patients, 12 and 20 of whom had prognostically distinct anaplastic oligodendroglioma and glioblastoma, respectively, was measured by PCR array. Next to unsupervised methods, we did supervised analysis using a weighted voting algorithm to construct a diagnostic system discriminating anaplastic oligodendroglioma from glioblastoma. The diagnostic accuracy of this system was evaluated by leave-one-out cross-validation. The clinical utility was tested on a microarray-based data set of 50 malignant gliomas from a previous study. RESULTS: Unsupervised analysis showed divergent global gene expression patterns between the two tumor classes. A supervised binary classification model showed 100% (95% confidence interval, 89.4-100%) diagnostic accuracy by leave-one-out cross-validation using 168 diagnostic genes. Applied to a gene expression data set from a previous study, our model correlated better with outcome than histologic diagnosis, and also displayed 96.6% (28 of 29) consistency with the molecular classification scheme used for these histologically controversial gliomas in the original article. Furthermore, we observed that histologically diagnosed glioblastoma samples that shared anaplastic oligodendroglioma molecular characteristics tended to be associated with longer survival. CONCLUSIONS: Our molecular diagnostic system showed reproducible clinical utility and prognostic ability superior to traditional histopathologic diagnosis for malignant glioma.