高通量测序筛查多巴反应性肌张力障碍家系突变基因

快速发展的高通量测序技术使遗传病家系突变基因的筛查鉴定成为可能,本研究通过全外显子测序、生物信息分析和PCR-测序技术筛选一个多巴反应性肌张力障碍(DRD)家系中可能的致病突变位点,从1 005个低频位点中选出在3个疾病个体至少有一个杂合突变的9个候选SNP,再通过DRD家系12个个体PCR扩增测序验证,新发现突变基因SLC18A1可能是该DRD家系的致病基因。此外,PCR和Sanger测序发现高通量外显子测序和信息分析的SNP分型准确性可高达96.3%,是一种遗传病家系突变基因筛查鉴定高效、准确的方法。     

中国人群中16个已知肺癌基因突变的综合性分析

目的:对过去已知的肺癌基因在中国人群中的突变分布进行综合性的分析,指导肺癌的临床治疗。方法:通过文献查阅,挑选出16个已知的肺癌基因。在112例肺癌样本中,对这16个基因进行大样本的靶基因测序并用Sanger测序来验证。同时,对突变在不同亚组中的分布差异进行分析。结果:16个已知肺癌基因突变可评价60.4%肺癌样本。同时,这些基因的在不同的样本亚组中表现出不同的突变特点;通过功能域的分析及蛋白空间结构的模拟,发现9个可能的突变热点既位于蛋白的功能域内又能导致蛋白空间结构或者表面电荷分布的异常。结论:通过靶基因深度测序,全面分析了16个已知肺癌基因在肺癌不同亚组中的突变分布差异,发现并初步验证了9个可能的肺癌突变热点。     

基于单细胞靶向测序探究基因碱基突变的方法

分析基因碱基突变是探究肿瘤细胞克隆演化的研究方法之一。目前,常取组织不同区域的群体细胞测序,基于群体水平的基因碱基突变频率等信息绘制出肿瘤的克隆演化过程。但是,该方法易遗失低频突变,并且组织群体细胞类型不单一,不能代表特定细胞群体的克隆演化过程。本研究以前列腺基底细胞癌(prostate basal cell carcinoma, BCC)为例,建立了一种探究肿瘤单细胞的基因碱基突变方法,实现了基于单细胞基因碱基突变分析肿瘤细胞的克隆演化过程。首先通过HepG2细胞优化了单细胞全基因组扩增方法,其次用Fluidigm公司的微流控芯片捕获BCC单细胞进行全基因组扩增,然后通过外显子组测序获得SCUBE3和MST1L基因碱基突变信息。通过单细胞靶向扩增和Sanger测序,成功在BCC单细胞中检测到SCUBE3和MST1L基因碱基突变信息。本研究建立的方法为肿瘤细胞的克隆演化研究提供了一种可靠的技术方案。     

肿瘤突变特征与病理分型的关联研究

准确评估肿瘤的病理亚型对诊断、治疗和预后至关重要。以往病理亚型的诊断主要依赖HE染色法和免疫组织化学法,而随着测序技术的不断发展,对患者进行基因型和表型特点的个体分析成为可能,将肿瘤病理分型与基因分型结合用于疾病分型、诊治选择和疗效判断的精准医学研究逐渐兴起。不同病理亚型的肿瘤细胞来源、致癌因素和临床表型均不尽相同,其在基因组上会留下特异“印迹”,即突变特征。本研究通过整合癌症基因组数据库(The Cancer Genome Atlas, TCGA)中肾癌、肺癌和食管癌的外显子测序数据,分别对3种肿瘤通过肿瘤基因突变特征进行肿瘤病理分型聚类和预测。首先通过非监督聚类方法将3种肿瘤分别按照24种突变特征进行聚类分析,其次通过随机森林法从24种突变特征中进一步选择对于区分不同病理亚型有显著性的突变特征并进行聚类分析,构建突变特征对3种肿瘤病理亚型的分型模型。在肾癌中,该模型准确率达到了100% (95% confidence interval (CI): 0.93~1.00),肺癌和食管癌中分别达到了78% (95% CI: 0.66~0.86)和84% (95% CI: 0.60~0.97)。以上研究结果表明,突变特征作为新型分子标记物,对肿瘤的病理分型、诊断,尤其是早诊具有一定的参考意义。     

利用基因芯片对一高保守基因进行肿瘤相关分析

本对大规模人类cDNA测序过程中获得的一条高保守基因进行了初步功能研究,生物信息学研究发现该基因在人类、小鼠、果蝇、拟南芥和裂殖酶母中都有很高的保守性,其他分析预测该基因可能具有肿瘤相关性。RT－PCR分析表明,该基因在成人和胎儿组织中广泛谱表达。利用基因芯片分析该基因在7例肝癌、5例胰腺癌、2例喉癌和2例肺癌中表达情况,结果证实了该基因的肿瘤相关性,并且提示该基因在不同类型中可能处于不同的地位。     

外显子组测序技术在人类疾病研究中的应用

外显子组测序是针对基因组中的蛋白质编码区,靶向富集外显子区域测序,以发现疾病相关遗传变异的技术。该技术近年越来越多地应用于发现人类基因组低频变异、鉴定单基因遗传病致病基因和肿瘤等复杂疾病易感基因研究,成为人类疾病相关变异研究的重要工具。综述了外显子组测序技术的基本原理及其在人类疾病相关基因研究中的应用。     

高通量测序技术在遗传性耳聋研究中的应用及研究进展

耳聋是一种常见的严重出生缺陷,阐明遗传性耳聋的致病机理不仅能够在临床上辅助诊断,为遗传咨询及耳聋预防提供依据,而且能促进人们更深入地了解耳聋的致病机制,开发新的治疗方法。随着基因组研究技术不断创新,以全基因组测序、全外显子组测序、目标区域测序为代表的高通量测序技术在遗传性耳聋研究中已得到广泛应用。本文总结了近5年全外显子组测序和目标区域测序在遗传性耳聋致病基因研究及临床分子诊断中应用及研究进展,希望能够有助于我国临床耳聋基因诊断技术的发展及诊断水平的提升。     

定位于1p36.12～1p35.1 的良性家族性婴儿惊厥家系 8 个候选基因的排除克隆*

目的:克隆定位于1p36.12～1p35.1上微卫星标志D1S2864和D1S2830之间12.4cM的区间内的腓骨肌萎缩症2L型的致病基因。方法:应用生物信息学方法筛选8个候选基因(NHE1、SMN、STX12、OX1R、BDR2、DHHC18、FLJ10315和SESN2),设计合成扩增8个基因外显子及外显子与内含子交界的引物,DNA直接测序法进行序列变异分析。结果:未发现与BFIS共分离的致病突变,但发现3个已知的多态。结论:排除了8个候选基因为该BFIS致病基因的可能。     

BRG1在肺癌组织和肿瘤细胞系中表达下调原因初探

前期的研究表明：在肺癌及多种肿瘤细胞系中,BRG1（brahma-related gene 1）的mRNA和蛋白质表达下调或缺失,但影响BRG1表达下调的原因并不清楚.因此,用PCR-SSCP（single strand conformation polymor-phism）方法检测18例肺癌组织和15株肿瘤细胞系DNA,并经测序证实：其中有1例肺癌组织的BRG1外显子25第3590位碱基存在T→C的点突变,其编码的BRG1蛋白第1171位氨基酸相应地由Val（缬氨酸）→Ala（丙氨酸）,该突变位于BRG1蛋白最重要的功能区（依赖DNA的ATP酶区）,提示BRG1突变在肺癌发生中可能起一定的作用.同时,对未检测到BRG1mRNA表达的6例肺癌组织和9株肿瘤细胞系还进行了DNA甲基化分析,结果发现：这些肺癌组织和肿瘤细胞系中BRG1启动子区均无异常甲基化.这说明BRG1在肺癌中表达下调的机制尚需进一步研究.     

组织中少量细胞的微卫星长度精细分析

微卫星是基因组上的特殊短重复序列,微卫星不稳定的程度与一些肿瘤的分型、治疗和预后相关。目前,微卫星长度变化的检测往往是基于大量细胞,检测灵敏度低。本文整合激光显微切割技术,基于多次退火环状循环扩增（multiple annealing and looping-based amplification cycles, MALBAC）的单细胞全基因组放大技术和毛细管电泳长度测量方法,经过关键技术点的改进,建立了一套针对组织中少量细胞的多微卫星位点检测方法。研究结果表明,基于技术改进,HE染色的组织细胞经激光显微切割分选后,可成功用MALBAC技术进行全基因组放大,并在多微卫星位点的检测上,获得了高度的准确性和重复性。利用所建立的方法,发现肠型胃癌早期病变组织-肠上皮化生（intestinal metaplasia, IM）的单个腺体内部出现多种长度变化的微卫星改变,说明该癌前病变组织中DNA错配修复系统已经出现问题。本方法所获得的全基因组放大产物,也可以用于外显子组测序和全基因组测序。另外,该方法适用于任何组织的少量细胞,甚至单细胞的多微卫星位点检测,以及全基因组的研究,为精细研究少量病变细胞的基因组特征以及组织异质性提供了有效的方法。     

整合分析基因表达与拷贝数变异识别癌症的驱动基因及调控子miRNAs

目的:通过整合分析基因的表达与拷贝数变异(CNV)识别癌症的驱动基因及调控子mi RNAs。方法:通过整合基因表达与CNV数据,分别计算了乳腺癌、结肠癌、肺癌、肾癌、膀胱癌、头颈癌六种癌症中mi RNAs的调控得分,提出了一个识别驱动基因和显著调控子mi RNAs的方法。结果:本文研究发现,CNV区域上编码的基因相比于非CNV区域上编码的基因更倾向于受mi RNAs调控。但是,癌相关CNV区域上的基因相比正常CNV区域上的基因更少受mi RNAs调控。本研究识别出了EXOSC4、ZNF7、BOP1等原癌基因,以及mi R-488、mi R-27a、mi R-454等在多种癌症中都起调控作用的调控子mi RNAs。结论:本文的方法为癌症研究带来了新的启发,这些具有调控扩增基因过表达作用的mi RNAs的发现,有助于我们更进一步了解癌基因表达的复杂调控机制,进而推动癌症的诊断、治疗和预后。     

Prediction of potential drivers connecting different dysfunctional levels in lung adenocarcinoma via a protein–protein interaction network

Lung cancer is a serious disease that threatens an affected individual's life. Its pathogenesis has not yet to be fully described, thereby impeding the development of effective treatments and preventive measures. “Cancer driver” theory considers that tumor initiation can be associated with a number of specific mutations in genes called cancer driver genes. Four omics levels, namely, (1) methylation, (2) microRNA, (3) mutation, and (4) mRNA levels, are utilized to cluster cancer driver genes. In this study, the known dysfunctional genes of these four levels were used to identify novel driver genes of lung adenocarcinoma, a subtype of lung cancer. These genes could contribute to the initiation and progression of lung adenocarcinoma in at least two levels. First, random walk with restart algorithm was performed on a protein–protein interaction (PPI) network constructed with PPI information in STRING by using known dysfunctional genes as seed nodes for each level, thereby yielding four groups of possible genes. Second, these genes were further evaluated in a test strategy to exclude false positives and select the most important ones. Finally, after conducting an intersection operation in any two groups of genes, we obtained several inferred driver genes that contributed to the initiation of lung adenocarcinoma in at least two omics levels. Several genes from these groups could be confirmed according to recently published studies. The inferred genes reported in this study were also different from those described in a previous study, suggesting that they can be used as essential supplementary data for investigations on the initiation of lung adenocarcinoma. This article is part of a Special Issue entitled: Accelerating Precision Medicine through Genetic and Genomic Big Data Analysis edited by Yudong Cai & Tao Huang.     

Proteomic signatures for histological types of lung cancer

We performed proteomic studies on lung cancer cells to elucidate the mechanisms that determine histological phenotype. Thirty lung cancer cell lines with three different histological backgrounds (squamous cell carcinoma, small cell lung carcinoma and adenocarcinoma) were subjected to two-dimensional difference gel electrophoresis (2-D DIGE) and grouped by multivariate analyses on the basis of their protein expression profiles. 2-D DIGE achieves more accurate quantification of protein expression by using highly sensitive fluorescence dyes to label the cysteine residues of proteins prior to two-dimensional polyacrylamide gel electrophoresis. We found that hierarchical clustering analysis and principal component analysis divided the cell lines according to their original histology. Spot ranking analysis using a support vector machine algorithm and unsupervised classification methods identified 32 protein spots essential for the classification. The proteins corresponding to the spots were identified by mass spectrometry. Next, lung cancer cells isolated from tumor tissue by laser microdissection were classified on the basis of the expression pattern of these 32 protein spots. Based on the expression profile of the 32 spots, the isolated cancer cells were categorized into three histological groups: the squamous cell carcinoma group, the adenocarcinoma group, and a group of carcinomas with other histological types. In conclusion, our results demonstrate the utility of quantitative proteomic analysis for molecular diagnosis and classification of lung cancer cells.     

Abberant methylation of p16, HIC1, N33 and GSTP1 genes in tumor epitelium and tumor-associated stromal cells of prostate cancer

The methylation status of four genes significant in prostate carcinogenesis p16, HIC1, N33 and GSTP1, were evaluated using quantitative methylationsensitive polymerase chain reaction. Tumor epithelia, tumor-associated stroma, normal epithelia, foci of PIN and benign prostate hyperplasia, and stroma adjacent to tumor tissues were isolated from whole-mount prostatectomy specimens of patients with localized prostate cancer by using laser capture microdissection. We found high levels of gene methylation in the tumor epithelium and tumor-associated stromal cells and some methylation in both hyperplastic epithelium and stromal cells in normal-appearing tissues located adjacent to tumors. Promoter methylation in the non-neoplastic cells of the prostate tumor microenvironment may play an important role in cancer development and progression. We examined the promoter methylation status of pl6, HIC1, N33 and GSTP1 in prostate biopsy fragments and prostate tissues after radical prostatectomy from patients with adenocarcinoma without laser capture microdissection. Methylation frequencies of all genes in tumor samples were considerably lower than frequencies in microdissected tumour samples (HIC1, 71 versus 89%; p16, 22 versus 78%; GSTP1, 32 versus 100%; N33, 20 versus 33%). The laser capture microdissection is required procedure in methylation studies taking into account multifocality and heterogenity of prostate cancer tissue.     

Mutation Analyses of 268 Candidate Genes in Human Tumor Cell Lines

We have performed a homozygous deletion screen on 268 candidate genes in 90 human tumor cell lines derived from multiple types of cancers. Most of the candidate genes investigated have been proposed to be involved in cellular processes that are germane to cancer progression, such as cell cycle control, genome maintenance, chromatin remodeling, cell adhesion, and apoptosis. We have detected novel homozygous deletions affecting four independent loci: Brahma-related gene (SMARCA4) on chromosome 19p in the TSU-Pr1 prostate and A427 lung carcinoma lines, Map Kinase Kinase 3 (MAP2K3) on 17q in the NCI-H774 lung tumor cell line, TMPRSS2 on 21q in the Bx PC-3 pancreatic carcinoma line, and Cadherin 6 (CDH6) on 5p in the SK-LU-1 lung carcinoma line. Subsequent analyses of the coding sequences of these four genes using cDNAs from a panel of tumor cell lines revealed multiple sequence variants. The results of this mutation study serve to demonstrate the feasibility of performing high-throughput screens of candidate genes in tumor cell lines to identify genes that may be targeted for mutation during the development of cancer.     

双向凝胶电泳-飞行时间质谱技术鉴定食管上皮细胞癌变时14-3-3 protein ε、S100A9的表达

[摘要] 目的：分析食管鳞癌和正常食管上皮细胞蛋白质的表达差异,获取鉴别两者的分子标志物。方法：通过激光捕获显微切割技术分离ESCC肿瘤细胞和癌旁上皮细胞,通过双向电泳和质谱技术鉴定表达异常的蛋白,并通过蛋白免疫印记证实部分差异蛋白的表达。结果：建立了食管癌组织和正常食管上皮蛋白的双向凝胶电泳图谱,通过质谱技术鉴定出14-3-3 protein ε、S100A9等蛋白在食管癌变时差异表达,蛋白印记结果证实14-3-3 protein ε、S100A9的表达量在食管癌变时分别上调和下调。结论：激光捕获显微切割是蛋白质组研究中的一个突破性的技术,可以有效地解决组织异质性的问题;本实验检测到的差异蛋白例如14-3-3 protein ε、S100A9可能成为鉴别食管癌组织和正常食管上皮特异性的分子标记物。     

Isolating bronchial epithelial cell preparations from gross lung specimens

Tissue microdissection is appropriate for separating pure cells from heterogeneous tissues. Recently, we have focused on whole genome DNA methylation patterns of lung squamous cell carcinoma (SCC) and needed to obtain the appropriate counterpart cells of lung SCC. However, in some regions of human tissues, such as in bronchial epithelium, it is difficult to apply tissue microdissection as a means to isolate pure cells from a heterogenous mixture of cells. Accordingly, we developed the pop brush method to retrieve sufficient amounts of pure bronchial epithelium from gross lung specimens, and this method enables us to study epigenetic variations of lung SCC.