微流控芯片在乳腺癌骨转移研究中的应用

乳腺癌骨转移患者死亡率高达70%～80%,目前缺乏有效的治疗药物.微流控芯片技术能够有效模拟骨组织的生化和生物物理微环境,便捷地实现模拟骨微环境中乳腺癌骨转移的研究,这将为探索乳腺癌骨转移的细胞和分子机制、进而进行抗乳腺癌骨转移药物高通量筛选提供有价值的技术方法和平台.本综述简要介绍了乳腺癌骨转移的分子机制和治疗药物研究现状,详细阐述了乳腺癌骨转移的微流控芯片模型,分析了基于微流控芯片技术进行抗乳腺癌骨转移药物高通量筛选的优势和挑战,旨在为乳腺癌骨转移机制研究和药物筛选提供参考.     

Multiplexed DNA Methylation Analysis in Colorectal Cancer Using Liquid Biopsy and Its Diagnostic and Predictive Value

Early diagnosis of colorectal cancer (CRC) is of high importance as prognosis depends on tumour stage at the time of diagnosis. Detection of tumour-specific DNA methylation marks in cfDNA has several advantages over other approaches and has great potential for solving diagnostic needs. We report here the identification of DNA methylation biomarkers for CRC and give insights in our methylation-sensitive restriction enzyme coupled qPCR (MSRE-qPCR) system. Targeted microarrays were used to investigate the DNA methylation status of 360 cancer-associated genes. Validation was done by qPCR-based approaches. A focus was on investigating marker performance in cfDNA from 88 patients (44 CRC, 44 controls). Finally, the workflow was scaled-up to perform 180plex analysis on 110 cfDNA samples, to identify a DNA methylation signature for advanced colonic adenomas (AA). A DNA methylation signature (n = 44) was deduced from microarray experiments and confirmed by quantitative methylation-specific PCR (qMSP) and by MSRE-qPCR, providing for six genes’ single areas under the curve (AUC) values of >0.85 (WT1, PENK, SPARC, GDNF, TMEFF2, DCC). A subset of the signatures can be used for patient stratification and therapy monitoring for progressed CRC with liver metastasis using cfDNA. Furthermore, we identified a 35-plex classifier for the identification of AAs with an AUC of 0.80.     

癌症液体活检新思路：数字PCR检测DNA甲基化

癌症的早期诊断可提高患者生存率.微创采集人体体液的液体活检方法可避免传统肿瘤组织活检方法侵入性和异质性的问题,逐渐成为癌症诊断的新方式.另外,DNA甲基化作为预测癌症发生发展的标志物,引起了越来越多研究者的关注.但传统DNA甲基化的检测方法灵敏度不高,且容易出现假阳性.近年来,数字PCR技术因其超高的检测灵敏度和精确度、无需标准曲线即可进行核酸绝对定量检测的优势,被用于DNA甲基化的定量检测中.本文首先介绍了DNA甲基化与癌症发生发展的关系,总结了传统DNA甲基化检测方法及其在癌症临床诊断中的应用,阐述了基于不同核酸样本分散方法的数字PCR技术及其在微量DNA甲基化检测中的优势,总结了采用数字PCR技术检测癌症患者体液中DNA甲基化的具体步骤,列举了数字PCR技术在癌症DNA甲基化检测中的研究成果及应用进展,最后提出了数字PCR技术检测癌症DNA甲基化未来可能面临的挑战,并对数字PCR技术在癌症液体活检方面的应用前景进行了展望.     

用聚丙烯酰胺凝胶电泳和微流体芯片电泳鉴别6种液态奶

目的:研究6种液态奶制品蛋白电泳图谱的区别,建立奶制品的蛋白质学鉴别方法。方法:以5种纯牛奶、羊奶、水牛奶、骆驼奶、牦牛奶、黄豆浆为研究对象,通过SDS-PAGE和Agilent 2100微流体芯片电泳法进行分析比较。结果:骆驼奶、黄豆浆与其他研究对象的图谱有明显区别,而牛奶、羊奶、水牛奶、牦牛奶的差异却不是很大;采用微流体芯片电泳可有效地对豆奶、骆驼奶进行区分,还可在一定程度上鉴别牛奶、羊奶、水牛奶和牦牛奶。结论:Agilent2100系统作为一种新型半自动微流体芯片技术,可以快速、高效、准确地应用于液态奶制品的蛋白成分分析及鉴别。     

表面增强拉曼散射技术无标记检测乳腺癌细胞来源外泌体

外泌体含有释放细胞的特异性物质,反映了释放细胞的组成成分,成为液体活检的重要物质。为了鉴别正常乳腺上皮细胞和乳腺癌细胞来源的外泌体,本研究采用表面增强拉曼(SERS)技术检测乳腺癌细胞MCF-7和人正常乳腺上皮细胞MCF-10A来源的外泌体,并且对比两种细胞外泌体的SERS光谱,筛选出相应的特征拉曼光谱。结果发现在800~1800 cm-1区域内,相对MCF-10A细胞,MCF-7来源的外泌体中归属于核酸的拉曼峰相对强度明显增高,且部分脂类峰强有所降低或部分特征峰消失,同时发现MCF-7还表现出其自己独特的拉曼谱型。此结果表明SERS技术可高灵敏度检测不同细胞来源的外泌体细微分子变化,可区分肿瘤细胞来源的外泌体与正常细胞来源的外泌体。SERS技术可作为癌症的早期检测和诊断的一种快速、无标记和无损的方法。     

Emerging technologies for salivaomics in cancer detection

Salivary diagnostics has great potential to be used in the early detection and prevention of many cancerous diseases. If implemented with rigour and efficiency, it can result in improving patient survival times and achieving earlier diagnosis of disease. Recently, extraordinary efforts have been taken to develop non‐invasive technologies that can be applied without complicated and expensive procedures. Saliva is a biofluid that has demonstrated excellent properties and can be used as a diagnostic fluid, since many of the biomarkers suggested for cancers can also be found in whole saliva, apart from blood or other body fluids. The currently accepted gold standard methods for biomarker development include chromatography, mass spectometry, gel electrophoresis, microarrays and polymerase chain reaction‐based quantification. However, salivary diagnostics is a flourishing field with the rapid development of novel technologies associated with point‐of‐care diagnostics, RNA sequencing, electrochemical detection and liquid biopsy. Those technologies will help introduce population‐based screening programs, thus enabling early detection, prognosis assessment and disease monitoring. The purpose of this review is to give a comprehensive update on the emerging diagnostic technologies and tools for the early detection of cancerous diseases based on saliva.     

Emerging Trends in Microfluidics Based Devices

One of the major challenges for scientists and engineers today is to develop technologies for the improvement of human health in both developed and developing countries. However, the need for cost‐effective, high‐performance diagnostic techniques is very crucial for providing accessible, affordable, and high‐quality healthcare devices. In this context, microfluidic‐based devices (MFDs) offer powerful platforms for automation and integration of complex tasks onto a single chip. The distinct advantage of MFDs lies in precise control of the sample quantities and flow rate of samples and reagents that enable quantification and detection of analytes with high resolution and sensitivity. With these excellent properties, microfluidics (MFs) have been used for various applications in healthcare, along with other biological and medical areas. This review focuses on the emerging demands of MFs in different fields such as biomedical diagnostics, environmental analysis, food and agriculture research, etc., in the last three or so years. It also aims to reveal new opportunities in these areas and future prospects of commercial MFDs.     

High-throughput lensfree imaging and characterization of a heterogeneous cell solution on a chip

A high-throughput on-chip imaging platform that can rapidly monitor and characterize various cell types within a heterogeneous solution over a depth-of-field of approximately 4 mm and a field-of-view of approximately 10 cm(2) is introduced. This powerful system can rapidly image/monitor multiple layers of cells, within a volume of approximately 4 mL all in parallel without the need for any lenses, microscope-objectives or any mechanical scanning. In this high-throughput lensless imaging scheme, the classical diffraction pattern (i.e., the shadow) of each micro-particle within the entire sample volume is detected in less than a second using an opto-electronic sensor chip. The acquired shadow image is then digitally processed using a custom developed "decision algorithm" to enable both the identification of the particle location in 3D and the characterization of each micro-particle type within the sample volume. Through experimental results, we show that different cell types (e.g., red blood cells, fibroblasts, etc.) or other micro-particles all exhibit uniquely different shadow patterns and therefore can be rapidly identified without any ambiguity using the developed decision algorithm, enabling high-throughput characterization of a heterogeneous solution. This lensfree on chip cell imaging platform shows a significant promise especially for medical diagnostic applications relevant to global health problems, where compact and cost-effective diagnostic tools are urgently needed in resource limited settings.     

Proteomic Analysis of Liquid Biopsy from Tumor-Draining Vein Indicates that High Expression of Exosomal ECM1 Is Associated with Relapse in Stage I-III Colon Cancer

BACKGROUND: The analysis of exosomes in blood obtained from the tumor-draining mesenteric vein (MV) can identify tumor biomarkers before they reach target organs and form the premetastatic niche where circulating tumor cells can anchor. Our group has recently shown that microRNAs in plasma from the MV—but not the peripheral vein (PV)—have been related to liver metastases in colon cancer (CC) patients. Here we examine the exosomal protein cargo in plasma from the MV and paired PV in 31 CC patients. PATIENTS AND METHODS: The study included patients who were initially diagnosed with stage I-III CC and 10 healthy controls. Exosomes from the MV and PV of all patients and controls were isolated by ultracentrifugation and confirmed by cryogenic transmission electron microscopy. High-throughput proteomic analysis by mass spectrometry was used to identify expression levels of exosomal proteins. Findings were confirmed by Western blot. RESULTS: Exosomal ECM1 protein was more highly expressed in patients than in controls and was 13.55 times higher in MV from relapsed than relapse-free patients. High exosomal ECM1 expression was associated with liver metastases. Patients with high exosomal ECM1 expression in MV—but not PV—plasma had shorter time to relapse than those with low ECM1 expression (P = .04). CONCLUSION: High levels of exosomal ECM1 protein can identify CC patients with a higher risk of relapse. The analysis of exosomes isolated from the tumor-draining MV is a promising method for the identification of biomarkers before they reach the target organ.