蛋白质芯片的制备及其在检测乙肝病毒中的应用

目的：建立一种用蛋白质芯片检测乙肝病毒抗原,抗体的新方法。方法：采用PVDF膜制备不同的蛋白质芯片,以辣根过氧化物酶标记抗全,结合酶联免疫反应,检测乙肝病毒素面抗原（HBsAg)。表面抗体（HBsAb),乙肝病毒e抗原（HBeAg),e抗体（HBeAb)。结果：所制备的蛋白质芯片可检没到微量乙肝病毒抗原,抗体的存在,其中HBsAg,HBsAb,HBeAg,HBeAb的最低可检测浓度分别为11μg/ml。4.8μg/ml,2.1μg/ml,18μg/ml,而且两种抗原或两种体间并城镇交叉反应,此法制备芯片需3.5h,而检测过程仅需20min,且结果直接可用肉眼观察。结论：将蛋白质芯片技术应用于乙肝病毒抗原,抗体的检测中,具有微量化,特异性强,快速灵敏,操作简便等优点,可望应用于临床乙肝“两对半”的检测中。     

SPR蛋白质芯片在输入性疟疾筛查中的应用

输入性疟疾已是我国疟疾防控的主要危险因素,如何对入境人员进行疟疾快速筛查是急需解决的难题。蛋白质芯片已被广泛应用于高通量筛选和诊断,本研究尝试构建了表面等离子共振技术 (Surface plasmon resonance,SPR) 蛋白芯片用于恶性疟疾的快速检测。采用聚乙二醇高分子处理的特异性吸附表面,以恶性疟疾特异性抗原富组氨酸蛋白Ⅱ (Histidine-rich protein Ⅱ,HRP2) 作为捕获探针,建立疟疾的微阵列芯片,并对芯片的最佳抗原固定浓度,检测的灵敏性和特异性,以及抗干扰能力进行了分析。该芯片可成功应用于恶性疟疾的筛查,具有无标记、即时快速的特点,与荧光定量PCR法相比,两种方法在敏感度和特异性方面无统计学差异。研究结果为一步研制疟疾分型鉴定蛋白质芯片奠定了基础,有利于对入境人员进行疟疾快速筛查。     

蛋白质微阵列检测抗原-抗体相互作用

为了制备蛋白质微阵列和研究芯片表面抗原-抗体的相互作用,研究了如何在玻片表面固化蛋白质和用荧光染料（Cy3,Cy5）对蛋白质进行标记.结果表明,在醛基修饰的玻璃表面,通过共价偶联的方法将抗原或抗体固定到芯片表面,能使二者保持其特异性结合能力.同时,荧光标记后的抗原或抗体仍然具有特异性结合能力.蛋白质微阵列是通过机械手在玻片表面排阵制作的.芯片上的荧光信号获取采用了激光共焦荧光扫描系统.用不同浓度的抗原探针阵列,对其相应的抗体靶分子的特异性结合进行了分析和研究.此外,还通过在玻片表面固定兔IgG和固定鼠IgG,对羊抗兔和羊抗鼠抗体与其相应抗原的特异性相互作用进行了检测.     

肿瘤自身抗体标志物的研究进展

肿瘤发生时,机体免疫系统针对肿瘤相关性抗原(tumor associated antigens,TAAs)产生免疫反应和自身抗体。大量研究表明,自身抗体在肿瘤发生早期可在血液中被检测到,因此在肿瘤早期诊断方面具有较大应用潜力。另外,自身抗体水平在肿瘤手术后显著性下降,因此自身抗体也可用于术后监测,并且由于肿瘤的异质性和个体差异,不同病人的自身抗体也可能存在差异,因此需以精准医疗的思想实施个体化监测。但目前,由于缺乏有效的工具,对肿瘤自身抗体的研究还较为落后,系统性地发现和鉴定肿瘤自身抗体存在较大挑战。蛋白质芯片,作为一个涵盖大量不同蛋白的抗原库,是一个全新的工具,为发现肿瘤自身抗体提供了有力的支撑。就肿瘤自身抗体标志物的应用潜力和研究方法进行了总结和评论。     

肿瘤抗原相关自身抗体的产生机制及其在肿瘤中的作用

肿瘤抗原相关自身抗体在肿瘤诊断、临床应用方面的价值是目前研究的重点。它不仅可以作为肿瘤早期诊断的生物标记,也可监测治疗效果、判断预后,但目前关于肿瘤抗原相关自身抗体产生机制的研究较少,深入研究其产生机制是阐明肿瘤抗原相关自身抗体促肿瘤或抑肿瘤作用的前提,也是今后研究的重点之一。本文就近年来肿瘤抗原相关自身抗体的产生机制、肿瘤早期诊断及其在肿瘤发生发展和预后中的应用进行总结,为积极寻找特异性强、灵敏度高的肿瘤抗原相关自身抗体及检测组合,明确肿瘤抗原相关自身抗体在不同肿瘤中的意义提供一定的理论参考。     

采用亲和层析结合制备凝胶电泳获得高纯度的重组抗原蛋白用于制备蛋白质芯片

为了得到制备抗原芯片所需的高纯度重组抗原蛋白,需要建立一套适合于多种重组抗原表达和纯化的技术路线．采用了亲和层析结合制备胶电泳的方法,对16种用于构建蛋白质芯片的食管癌相关抗原基因进行了克隆重组并在大肠杆菌中进行了表达．对高表达的重组蛋白首先制备包涵体,然后采用Ni-Sepharose亲和层析得到初步纯化的蛋白质,最后使用SDS-PAGE制备胶电泳作进一步纯化．经过透析复性后,用于制备蛋白质芯片．采用亲和层析纯化重组蛋白,得率为71% ,纯度约为70%;在SDS-PAGE制备胶进一步纯化后,得率为32%,纯度为95%,经过透析和复性后,最终得率为21%,纯度为95%．得到的重组蛋白RPS4在ELISA检测中可以和血清中识别RPS4 的自身抗体起反应,并且,采用精纯抗原制备的蛋白质芯片,在检测抗原与抗体这一对反应中也具有较高的敏感性和特异性,适合大规模血清抗体的检测．研究表明,采用亲和层析结合制备凝胶电泳纯化抗原蛋白,是一条简便快捷,适合需要量不大,但对纯度要求比较高的蛋白质芯片制备的技术路线．     

蛋白质芯片技术应用于高通量单克隆抗体制备研究

针对在传统的单克隆抗体制备过程中进行特异性筛选时大量的人力消耗,建立了一种联合应用蛋白质芯片进行单克隆抗体制备的方法。用8种重组蛋白分别免疫BALB/c小鼠,在传统的细胞融合的基础上,将8种抗原免疫的杂交瘤阳性细胞混合后进行克隆化、蛋白质芯片筛选,阳性细胞有限稀释克隆化制备相关抗体。实验结果：混合克隆化共得到单克隆细胞175孔,经蛋白质芯片筛选出阳性孔119孔,选择针对单一抗原阳性的细胞连续2轮克隆化,8种重组蛋白各获得单克隆抗体细胞株1株。与经典的单克隆抗体制备相比,蛋白质芯片筛选与混合克隆化技术联合应用于单克隆抗体制备,1个筛选周期获得了8种重组蛋白的单克隆抗体细胞株,提高了单克隆抗体的制备效率,节省了在筛选中的抗原用量,提供了一种经济、快速、简便的方法。     

蛋白质芯片技术应用于高通量单克隆抗体制备研究

针对在传统的单克隆抗体制备过程中进行特异性筛选时大量的人力消耗,建立了一种联合应用蛋白质芯片进行单克隆抗体制备的方法。用8种重组蛋白分别免疫BALB/c小鼠,在传统的细胞融合的基础上,将8种抗原免疫的杂交瘤阳性细胞混合后进行克隆化、蛋白质芯片筛选,阳性细胞有限稀释克隆化制备相关抗体。实验结果:混合克隆化共得到单克隆细胞175孔,经蛋白质芯片筛选出阳性孔119孔,选择针对单一抗原阳性的细胞连续2轮克隆化,8种重组蛋白各获得单克隆抗体细胞株1株。与经典的单克隆抗体制备相比,蛋白质芯片筛选与混合克隆化技术联合应用于单克隆抗体制备,1个筛选周期获得了8种重组蛋白的单克隆抗体细胞株,提高了单克隆抗体的制备效率,节省了在筛选中的抗原用量,提供了一种经济、快速、简便的方法。     

蛋白质芯片技术研究进展

蛋白质芯片技术是近年发展起来的一项新技术,这项技术是将蛋白质的分析微缩到小型芯片上进行,利用荧光或酶显色进行探测,最后用特 计算机软件加以分析。该技术在基因表达、抗原抗体检测、药物开发、疾病诊断等研究方面显示出快速、高效、高通量处理信息的能力。     

丙型肝炎病毒分片段抗体检测蛋白质芯片的制备及临床评价

为了制备丙型肝炎病毒分片段抗体检测蛋白质芯片,并对其临床应用价值进行评价,将基因工程表达的丙型肝炎病毒分片段抗原,点至经特殊处理的玻片上,制成蛋白质芯片.收集来自三家临床单位用于临床验证的905份血清标本.分别用丙肝病毒分片段抗体检测蛋白质芯片、ELISA丙肝病毒抗体检测试剂进行检测.部分样本同时采用进口RIBA抗体检测试剂进行了检测,分别比较蛋白质芯片法与ELISA法以及RIBA试剂的符合率.结果表明：a.905份血清标本,ELISA法检出阳性294份,阴性611份.阳性标本用蛋白质芯片法检测,融合抗原292份显示阳性结果、2份阴性结果,根据蛋白质芯片的核心抗原,以及NS3, NS4,NS5分片段抗原综合判断确定阳性样本288份阳性,阴性样本2份,4份样本结果不确定.ELISA法检出的611份阴性标本用两种蛋白质芯片法检测,检出阴性均为611份.两种蛋白质芯片法与ELISA法的阳性符合率分别为99.3%和98.9%,与ELISA法的阴性符合率均为100%.用RIBA 试剂检测6份ELISA法为阳性,蛋白质芯片法为非阳性的样本,结果均为非阳性.b.290份经 RIBA试剂确认的阳性标本104份,单片段阳性标本66份,阴性标本120份,用蛋白质芯片法检测,检出阳性标本103份,单片段阳性标本61份,阴性标本126份,二者具有很高的符合率（P＞0.01）.丙型肝炎病毒分片段抗体检测蛋白质芯片,检测灵敏度和特异性高于ELISA法,对血清样本的确认程度与进口的RIBA试剂高度一致,具有操作简便,费用低廉的特点,是一种新型、高效的体外诊断试剂.     

Autoantibody biomarkers in the detection of cancer

By definition, tumor biomarkers are selective molecules that can distinguish between patients with cancer and controls. Serum tumor markers have been the most widely used approach for cancer detection. However, the limitations of these markers, which are based on the measurement of tumor antigens, preclude their general use in cancer screening and diagnosis. Here we give an overview of recent cancer biomarker developments based on the detection of autoantibodies produced against tumor antigens in patients' sera. This new detection method can measure the autoantibodies for a spectrum of tumor antigens in a single assay, with sensitivity and specificity exceeding those obtained using the conventional antigen determination method. Autoantibodies against serum cancer biomarkers offer a novel technology for cancer detection.     

Autoantibody biomarker opens a new gateway for cancer diagnosis

The list of cancer markers of current interest has grown considerably, but none of the markers used in clinical work is a true tumor marker. These cancer biomarkers are based on the determination of tumor antigens. Here, we report a single method of autoantibody enzyme immunoassay (EIA) screens for a spectrum of serum tumor markers. A comparison of the autoantibody-based EIA to conventional antigen EIA kits, using receiver operating characteristic (ROC) plots, showed that the autoantibody EIA can significantly enhance the sensitivity and specificity of tumor markers. The detection of serum autoantibodies for a spectrum of serum tumor markers, as demonstrated here, suggests that most, if not all, serum cancer biomarkers produce autoantibodies. A unique autoantibody biomarker screening method, as presented here, might therefore facilitate achieving the accurate and early diagnosis of cancer.     

Serum Autoantibodies in Chronic Prostate Inflammation in Prostate Cancer Patients

Background

Chronic inflammation is frequently observed on histological analysis of malignant and non-malignant prostate specimens. It is a suspected supporting factor for prostate diseases and their progression and a main cause of false positive PSA tests in cancer screening. We hypothesized that inflammation induces autoantibodies, which may be useful biomarkers. We aimed to identify and validate prostate inflammation associated serum autoantibodies in prostate cancer patients and evaluate the expression of corresponding autoantigens.

Methods

Radical prostatectomy specimens of prostate cancer patients (N = 70) were classified into high and low inflammation groups according to the amount of tissue infiltrating lymphocytes. The corresponding pre-surgery blood serum samples were scrutinized for autoantibodies using a low-density protein array. Selected autoantigens were identified in prostate tissue and their expression pattern analyzed by immunohistochemistry and qPCR. The identified autoantibody profile was cross-checked in an independent sample set (N = 63) using the Luminex-bead protein array technology.

Results

Protein array screening identified 165 autoantibodies differentially abundant in the serum of high compared to low inflammation patients. The expression pattern of three corresponding antigens were established in benign and cancer tissue by immunohistochemistry and qPCR: SPAST (Spastin), STX18 (Syntaxin 18) and SPOP (speckle-type POZ protein). Of these, SPAST was significantly increased in prostate tissue with high inflammation. All three autoantigens were differentially expressed in primary and/or castration resistant prostate tumors when analyzed in an inflammation-independent tissue microarray. Cross-validation of the inflammation autoantibody profile on an independent sample set using a Luminex-bead protein array, retrieved 51 of the significantly discriminating autoantibodies. Three autoantibodies were significantly upregulated in both screens, MUT, RAB11B and CSRP2 (p>0.05), two, SPOP and ZNF671, close to statistical significance (p = 0.051 and 0.076).

Conclusions

We provide evidence of an inflammation-specific autoantibody profile and confirm the expression of corresponding autoantigens in prostate tissue. This supports evaluation of autoantibodies as non-invasive markers for prostate inflammation.     

肺鳞状细胞癌发生的早期标志物及肿瘤预测模型

选取癌症基因组图谱数据库的肺鳞状细胞癌(Lung Squamous Cell Carcinoma,LUSC)样本作为数据集,在全基因组的水平上研究肺鳞状细胞癌病人从正常到发病I期基因表达的变化,寻找与LUSC发病密切相关的早期标志物,并建立一种基于早期标志基因的肿瘤预测模型。方法 采用模式识别分类法和基因通路和功能分析相结合的筛选方法,对LUSC的早期标志物进行识别,并运用Fisher判别建立肿瘤预测模型。得到12个LUSC的早期标志物,分别是CLDN18, CD34, ESAM, JAM2, CDH5, F11, F8, CFD, MRC1, MARCO, SFTPA2 和 SFTPA1,机器学习建模后对LUSC早期癌症样本和正常肺组织样本的分类精度达到了98%以上。由基因SFTPA1和ESAM建立的LUSC早期肿瘤预测模型,对正常肺组织和LUSC肿瘤Ⅰ期样本的分类敏感性和特异性分别为99.18%和100%,并且独立验证集的分类准确率也在90%以上。结论 筛选出的12个早期分子标志物有望成为LUSC诊断的标志分子,并且建立的肿瘤预测模型具有极高的准确性,可以为LUSC的发生机理研究以及早期肿瘤预测提供帮助。     

核酸适配体在三阴性乳腺癌诊疗中的研究进展*

乳腺癌是女性高发恶性肿瘤,三阴性乳腺癌(triple-negative breast cancer, TNBC)恶性程度极高,且发病机制复杂,是乳腺癌分型中预后最差的类型,但目前其早期筛查和诊断的敏感度仍处在较低水平。因此,亟须通过应用具有高度特异性的肿瘤标志物分子探针,实现其早期诊断和治疗。核酸适配体是在人工合成的随机单链核酸序列文库中,通过指数富集的配体系统进化技术(systematic evolution of ligands by exponential enrichment, SELEX)筛选获得的寡核苷酸序列。高效的分子识别能力使其成为最具潜力的生物靶向分子,在肿瘤诊断及治疗中具有广阔的应用前景。目前,通过筛选已获得了多种靶向TNBC细胞的核酸适配体。重点综述基于SELEX及其衍生技术筛选TNBC相关核酸适配体的新进展,以及核酸适配体在TNBC诊断和治疗中的应用,为相关研究提供参考。     

A Meta Analysis of Pancreatic Microarray Datasets Yields New Targets as Cancer Genes and Biomarkers

The lack of specific symptoms at early tumor stages, together with a high biological aggressiveness of the tumor contribute to the high mortality rate for pancreatic cancer (PC), which has a five year survival rate of less than 5%. Improved screening for earlier diagnosis, through the detection of diagnostic and prognostic biomarkers provides the best hope of increasing the rate of curatively resectable carcinomas. Though many serum markers have been reported to be elevated in patients with PC, so far, most of these markers have not been implemented into clinical routine due to low sensitivity or specificity. In this study, we have identified genes that are significantly upregulated in PC, through a meta-analysis of large number of microarray datasets. We demonstrate that the biological functions ascribed to these genes are clearly associated with PC and metastasis, and that that these genes exhibit a strong link to pathways involved with inflammation and the immune response. This investigation has yielded new targets for cancer genes, and potential biomarkers for pancreatic cancer. The candidate list of cancer genes includes protein kinase genes, new members of gene families currently associated with PC, as well as genes not previously linked to PC. In this study, we are also able to move towards developing a signature for hypomethylated genes, which could be useful for early detection of PC. We also show that the significantly upregulated 800+ genes in our analysis can serve as an enriched pool for tissue and serum protein biomarkers in pancreatic cancer.     

Enhanced detection of autoantibodies on protein microarrays using a modified protein digestion technique

High-throughput studies to determine differential immune (humoral) response to diseases are becoming of increasing interest because the information they provide can help in early diagnosis as well as monitoring of therapeutics. Protein microarrays are a high-throughput and convenient technology that can be applied to the study of the humoral response. Proteins can be arrayed on slides and then probed with serum from different classes of patients to observe differences that may exist among autoantibodies that reflect differences in disease states. However, such studies may be difficult to interpret due to the weak overall signal response of such protein microarrays. We propose that this weak signal response is due to the physical positioning of the disease proteins that renders them sterically hindered from binding partners in the serum. In this study, we hypothesize that reducing the complexity and size of the disease proteins by chemical digestion using cyanogen bromide (CNBr) may enhance the overall signal from the humoral response and facilitate visualization of disease-specific responses in various classes of serum. A modified protein microarray methodology using CNBr digestion is presented here. The new workflow was applied to a set of 10 serum samples from healthy subjects, 10 from patients with chronic pancreatitis and 10 from patients diagnosed with pancreatic cancer and the results were compared to results obtained in the absence of CNBr digestion. CNBr digestion allowed the identification of 10 additional autoantibodies that responded to serum, 5 of which were unique to pancreatitis and cancer sera. This new methodology may increase the sensitivity of microarray studies measuring autoantibodies in serum.     

GP73 与消化系统疾病的研究进展

高尔基体是一个非常重要的细胞器,最近研究表明,它除了蛋白加工外,还能参与细胞分化、细胞间信号传导和细胞凋亡, 其功能障碍也许和疾病的发生、发展有着某种联系。随着蛋白组学技术的发展,使得筛选新的肿瘤标志物成为可能,其中高尔基 体蛋白73（GP73）被认为是最值得期待的血清标志物之一,尤其是早期肝癌的血清标志物。本文对近年来有关GP73 结构、表达分 布以与及消化系统疾病的研究进展进行综述。     

Molecular-genetic markers in lung cancer diagnostics

The major approaches to different lung cancer marker development are outlined in the review, including genetic, epigenetic, protein, transcryptomic, proteomic, metabolic, and miRNA markers. As far as epigenetic changes are among the earliest events in malignant transformation, methylated markers are thoroughly discussed. Special attention is given to minimally invasive tumor markers, which could be detected in easily accessible biological fluids, because they can be useful for screening and early diagnostics of cancer (before its clinical manifestation) as well as for verification of standard methods of diagnostics. Extracellular nucleic acids, circulating in blood (cirNA), are highlighted as the potential source of material for the early lung cancer diagnostics, prediction of antitumor treatment efficiency, post-treatment monitoring and disease prognosis.