Lipidomic study and diagnosis of hepatocellular carcinoma tumor with rapid evaporative ionization mass spectrometry

Liver cancer is generally considered the leading cause of cancer deaths worldwide, and hepatocellular carcinoma (HCC) contributes to more than 90% of liver cancers. The altered lipid metabolism for rapid cancer cell growth and tumor formation has been frequently proven. In this study, an ambient ionization mass spectrometry technique, rapid evaporative ionization mass spectrometry (REIMS) using a monopolar electric knife, called iKnife, was systematically optimized and employed for ex vivo analysis of 12 human HCC tumor tissue specimens together with the paired paracancerous tissue (PT) and noncancerous liver tissue (NCT) specimens. Nine free fatty acids and 34 phospholipids were tentatively identified according to their extract masses and/or tandem mass spectra. With the help of statistical methods, 7 free fatty acids and 10 phospholipids were distributed differently in 3 types of liver tissue specimens (95% confidence interval). The box plots showed these characterized lipid metabolites varied in PT, HCC, and NCT. Compared with PT and NCT, the upregulations of four common fatty acids FA 18:0, FA 20:4, FA 16:0, and FA 18:1, together with phospholipids PC 36:1, PE 38:3, PE (18:0/20:4), PA (O-36:1), PC (32:1), PC 32:0, PE 34:0, and PC (16:0/18:1), were found in HCC specimens. The sensitivity and specificity of the established statistic model for real-time HCC tumor diagnosis were 100% and 90.5%, respectively. This study demonstrated that the described REIMS technique is a potential method for rapid lipidomic analysis and characterization of HCC tumor tissue.     

基于代谢组学技术的快速蒸发电离质谱与智能手术刀联用实时鉴别果汁掺伪方法研究

近年来,果汁掺伪问题日益突出。作为一种新型的实时鉴别方法,智能手术刀(IKnife)与快速蒸发电离质谱(REIMS)联用技术无需样品前处理即可解决这一问题。该文采用代谢组学指纹识别技术建立橙汁、苹果汁和葡萄汁的实时鉴别方法,并对其掺假水平进行预测。主成分分析-线性判别分析联用法建立的判别模型能够区分不同类型的果汁,排除20%交叉验证法的正确率为97.28%,未知样品实时鉴别正确率高达100%。筛选出不同果汁中的标志物,并对部分化合物进行鉴定。结果表明,此方法能够成功区分掺有10%-50%苹果汁和葡萄汁的橙汁。通过对比分析REIMS单极质谱和串联质谱(REIMS/MS)的检测结果,两种方法建立的偏最小二乘分析模型均能准确预测掺假水平(所有模型的R 2和Q 2均大于0.82)。与传统的REIMS方法相比,REIMS/MS的预测值更加精确。     

快速蒸发电离质谱技术及其应用研究进展

近年来,原位电离质谱技术成为质谱分析领域的研究前沿和热点。快速蒸发电离质谱技术源于外科手术中的手术烟雾现象,自2009年报道以来,作为一种新型原位电离质谱技术已被广泛应用于医学、微生物鉴定、食品真伪鉴别、代谢物研究、药用植物成分鉴定等领域。该技术通过电离切割组织或其他生物样品产生的含丰富特定区域生物特征的气溶胶,对其进行原位、在线、实时、快速质谱分析。该文阐述了快速蒸发电离质谱技术的发展历程、电离机制及工作原理,并对其在不同领域的应用研究进展进行了综述,可为相关领域研究人员提供科研思路和技术参考。     

Lipidomic analysis and diagnosis of glioblastoma multiforme with rapid evaporative ionization mass spectrometry

Glioblastoma multiforme (GBM) is the most common and aggressive brain tumor in the central nervous system. GBM patients have a very low 5-year survival rate and most of them died within 1 year. Conventional histopathological examination for GBM diagnosis is complicated and time-consuming, which always blocks the development of more precise and effective treatments in resection operation. Rapid evaporative ionization mass spectrometry (REIMS) is a MS technique in clinical medicine research, which combines the common diathermy device with MS to acquire the lipid profiles of tissue specimens for lipidomic analysis and real-time tumor diagnosis. In this study, the REIMS method employing bipolar forceps was optimized and validated for high-throughput lipidomics and diagnosis of GBM for the first time. Total 42 lipid metabolites were tentatively identified and 12 out of 13 lipid biomarkers showed higher intensities in GBM, which were consistent with previous studies. After this, a statistic model was built with the lipidomic data for the diagnosis of GBM tumor in real-time. The diagnostic accuracy (94.74%), sensitivity (95.38%), and specificity (93.33%) were evaluated with histopathology validated brain tissue specimens that were not used in the training set. The proposed REIMS method for the lipidomic-analysis and diagnosis of GBM tumor provides a new direction for MS-based lipidomics and precision medicine and might be used to guide surgeons to precisely resect the GBM tissue and keep the normal brain tissue in operation.     

Real-time traceability of sorghum origin by soldering iron-based rapid evaporative ionization mass spectrometry and chemometrics

Sorghum is an important grain with a high economic value for liquor production. Tracing the geographical origin of sorghum is vital to guarantee the liquor flavor. Soldering iron-based rapid evaporative ionization mass spectrometry (REIMS) combined with chemometrics was developed for the real-time discrimination of the sorghum's geographical origin. The working conditions of soldering iron-based ionization were optimized, and then the obtained MS profiling data were processed using chemometrics analysis methods, including principal component analysis–linear discriminant analysis and orthogonal projection to latent structures discriminant analysis (OPLS-DA). A recognition model was established, and discriminations of sorghum samples from 10 provinces in China were achieved with a correct rate higher than 90%. On the basis of OPLS-DA, the specific ions of m/z 279.2327, 281.2479, and 283.2639 had relatively strong discrimination power for the geographical origins of sorghum. The developed method was successfully applied in the discrimination of sorghum origins. The results indicated that the soldering iron-based REIMS technique combined with chemometrics is a useful tool for direct, fast, and real-time ionization of poor conductivity samples and acquisition of metabolic profiling data.     

Evaluation of Raman probe for oesophageal cancer diagnostics

Early detection of (pre-)cancerous changes improves prognosis, therefore in the UK patients at high risk of developing gastrointestinal cancers are enrolled on endoscopic surveillance programmes or the Bowel Cancer Screening Programme. The current gold standard technique for the detection of pre-cancerous changes in the gastrointestinal tract is histopathological analysis of biopsy tissue collected at endoscopy. This relies upon subjective assessment of morphological changes within the excised tissue samples and poor targeting of pre-malignant lesions. Raman spectroscopy offers a number of potential advantages for in vivo assessment of tissue at endoscopy. The performance of a custom built Raman probe as a biopsy targeting tool has been evaluated using excised biopsy material. Multivariate classification models have been used to demonstrate the likely ability of a miniature, confocal, fibre optic Raman probe to be used as an optical biopsy tool at endoscopy to provide spectral information in clinically practicable timescales. This technique could facilitate improved targeting of excisional biopsy with associated clinical benefits.     

Multivariate statistical identification of human bladder carcinomas using ambient ionization imaging mass spectrometry

Diagnosis of human bladder cancer in untreated tissue sections is achieved by using imaging data from desorption electrospray ionization mass spectrometry (DESI-MS) combined with multivariate statistical analysis. We use the distinctive DESI-MS glycerophospholipid (GP) mass spectral profiles to visually characterize and formally classify twenty pairs (40 tissue samples) of human cancerous and adjacent normal bladder tissue samples. The individual ion images derived from the acquired profiles correlate with standard histological hematoxylin and eosin (H&E)-stained serial sections. The profiles allow us to classify the disease status of the tissue samples with high accuracy as judged by reference histological data. To achieve this, the data from the twenty pairs were divided into a training set and a validation set. Spectra from the tumor and normal regions of each of the tissue sections in the training set were used for orthogonal projection to latent structures (O-PLS) treated partial least-square discriminate analysis (PLS-DA). This predictive model was then validated by using the validation set and showed a 5% error rate for classification and a misclassification rate of 12%. It was also used to create synthetic images of the tissue sections showing pixel-by-pixel disease classification of the tissue and these data agreed well with the independent classification that uses histological data by a certified pathologist. This represents the first application of multivariate statistical methods for classification by ambient ionization although these methods have been applied previously to other MS imaging methods. The results are encouraging in terms of the development of a method that could be utilized in a clinical setting through visualization and diagnosis of intact tissue.     

敞开式离子化质谱技术及其在微生物分析中的应用

敞开式离子化质谱(Ambient ionization mass spectrometry,AI-MS)是近年来兴起的质谱分析技术,可在敞开的大气环境下实现离子化,无需或只需少许样品前处理步骤,具有实时、简便、快速、高通量等诸多优点。近年来AI-MS技术的发展与应用已成为质谱领域备受关注的热点之一。该文综述了AI-MS的技术分类与原理特点,总结了AI-MS在微生物领域的应用。重点介绍了AI-MS在微生物种属鉴定与分型、微生物代谢物分析与生物膜分析、质谱成像等领域的应用。目前,环境电离与便携式质谱仪相结合已得到越来越广泛的应用,即将成为质谱领域的新热点。     

Electrospray Post-Ionization Mass Spectrometry of Electrosurgical Aerosols

The feasibility of electrospray (ES) ionization of aerosols generated by electrosurgical disintegration methods was investigated. Although electrosurgery itself was demonstrated to produce gaseous ions, post-ionization methods were implemented to enhance the ion yield, especially in those cases when the ion current produced by the applied electrosurgical method is not sufficient for MS analysis. Post-ionization was implemented by mounting an ES emitter onto a Venturi pump, which is used for ion transfer. The effect of various parameters including geometry, high voltage setting, flow parameters, and solvent composition was investigated in detail. Experimental setups were optimized accordingly. ES post-ionization was found to yield spectra similar to those obtained by the REIMS technique, featuring predominantly lipid-type species. Signal enhancement was 20- to 50-fold compared with electrosurgical disintegration in positive mode, while no improvement was observed in negative mode. ES post-ionization was also demonstrated to allow the detection of non-lipid type species in the electrosurgical aerosol, including drug molecules. Since the tissue specificity of the MS data was preserved in the ES post-ionization setup, feasibility of tissue identification was demonstrated using different electrosurgical methods.     

FeOOH@Metal–Organic Framework Core–Satellite Nanocomposites for the Serum Metabolic Fingerprinting of Gynecological Cancers

High-throughput metabolic analysis is of significance in diagnostics, while tedious sample pretreatment has largely hindered its clinic application. Herein, we designed FeOOH@ZIF-8 composites with enhanced ionization efficiency and size-exclusion effect for laser desorption/ionization mass spectrometry (LDI-MS)-based metabolic diagnosis of gynecological cancers. The FeOOH@ZIF-8-assisted LDI-MS achieved rapid, sensitive, and selective metabolic fingerprints of the native serum without any enrichment or purification. Further analysis of extracted serum metabolic fingerprints successfully discriminated patients with gynecological cancers (GCs) from healthy controls and also differentiated three major subtypes of GCs. Given the low cost, high-throughput, and easy operation, our approach brings a new dimension to disease analysis and classification.     

Recent advances of ambient ionization mass spectrometry imaging in clinical research

The structural information and spatial distribution of molecules in biological tissues are closely related to the potential molecular mechanisms of disease origin, transfer, and classification. Ambient ionization mass spectrometry imaging is an effective tool that provides molecular images while describing in situ information of biomolecules in complex samples, in which ionization occurs at atmospheric pressure with the samples being analyzed in the native state. Ambient ionization mass spectrometry imaging can directly analyze tissue samples at a fairly high resolution to obtain molecules in situ information on the tissue surface to identify pathological features associated with a disease, resulting in the wide applications in pharmacy, food science, botanical research, and especially clinical research. Herein, novel ambient ionization techniques, such as techniques based on spray and solid‐liquid extraction, techniques based on plasma desorption, techniques based on laser desorption ablation, and techniques based on acoustic desorption were introduced, and the data processing of ambient ionization mass spectrometry imaging was briefly reviewed. Besides, we also highlight recent applications of this imaging technology in clinical researches and discuss the challenges in this imaging technology and the perspectives on the future of the clinical research.     

In vivo protein sampling using capillary ultrafiltration semi-permeable hollow fiber and protein identification via mass spectrometry-based proteomics

Here, we advanced a novel technique using capillary ultrafiltration (CUF) probes to collect in vivo secreted proteins in the subcutaneous tissue of mouse ear. We fabricated two kinds of CUF probe, one with and one without a semi-permeable membrane hollow fiber. Proteins collected by CUF probes were profiled and identified by matrix-assisted laser desorption/ionization time-of-flight mass spectrometer (MADLI-TOF-MS) and quadrupole time-of-flight tandem mass spectrometry (Q-TOF-MS/MS) without using two-dimensional gel electrophoresis (2-DE) separation. Five proteins including cofilin-1, futuin-A, complement C3, gelsolin, and apolipoprotein C-1 were identified from the sample collected by the CUF probe with a semi-permeable membrane hollow fiber. The presence of well documented secretory proteins supports the efficiency of CUF probes in sampling in vivo secreted proteins. We also found that hemoglobin collected by the CUF probe without a semi-permeable membrane hollow fiber completely masked protein identification by mass spectrometry. The presence of relatively large amounts of hemoglobin in this condition illustrates the necessity of the semi-permeable membrane hollow fiber to the technique of CUF probe in conjunction with mass spectrometry. Also, the technique represents a powerful method for the identification of in vivo secreted proteins and has potential application for in the detection of biomarkers for human diseases.     

敞开式离子化质谱在贸易产品化学风险物质筛查中的应用及前景

敞开式离子化质谱是一种新兴的质谱快检技术,具有分析速度快、操作流程简单、特异性强等特点。该技术无需对样品做复杂预处理,尤其在与便携式质谱仪联用时,可用于大量样品的现场、快速、准确筛查,在贸易产品化学风险物质的筛查中展现出广泛的应用前景。该文主要综述敞开式离子化质谱近年来在贸易产品化学风险物质筛查方面的研究进展,并对其未来的发展前景进行了展望。     

A technique for relative quantitation of cancer biomarkers in formalin‐fixed,paraffin‐embedded (FFPE) tissue using stable‐isotope‐label based mass spectrometry imaging (SILMSI)

We developed a novel technique for the relative quantitation of pairs of cancer biomarkers in formalin‐fixed paraffin‐embedded (FFPE) tissue. The method utilizes stable isotope labeled (SIL) chromogens deposited during the standard immunohistochemistry (IHC) tissue staining process. The labeled chromogens are precipitated on tissue enzymatically using the standard IHC protocols. The tissue is then imaged with matrix‐free laser desorption ionization time‐of‐flight mass spectrometry, and peak intensities of reporter ions are used to estimate the relative quantitation of protein biomarkers across the tissue. The relative abundance of two breast cancer biomarkers, estrogen receptor (ER) and progesterone receptor (PgR), were quantitated using their ratio of expression in xenograft models, and the ratios were found to be reproducible both within and across serial sections. The relative quantification of multiple biomarkers in situ across a single tissue section adds an additional dimension in cancer histological evaluation by allowing a visual and statistical assessment of tumor heterogeneity. Copyright © 2015 John Wiley & Sons, Ltd.     

FeOOH@Metal–Organic Framework Core–Satellite Nanocomposites for the Serum Metabolic Fingerprinting of Gynecological Cancers

High‐throughput metabolic analysis is of significance in diagnostics, while tedious sample pretreatment has largely hindered its clinic application. Herein, we designed FeOOH@ZIF‐8 composites with enhanced ionization efficiency and size‐exclusion effect for laser desorption/ionization mass spectrometry (LDI‐MS)‐based metabolic diagnosis of gynecological cancers. The FeOOH@ZIF‐8‐assisted LDI‐MS achieved rapid, sensitive, and selective metabolic fingerprints of the native serum without any enrichment or purification. Further analysis of extracted serum metabolic fingerprints successfully discriminated patients with gynecological cancers (GCs) from healthy controls and also differentiated three major subtypes of GCs. Given the low cost, high‐throughput, and easy operation, our approach brings a new dimension to disease analysis and classification.     

飞行时间质谱仪新技术的进展及应用

本文介绍了近几年来发展应用于飞行时间质谱(TOF-MS)仪中的软电离技术。质子转移电离实现了可挥发性有机物的高灵敏度分析;真空紫外灯电离源体积小、简单,利于便携式仪器;电喷雾解吸电离在线、无损和灵敏度高,在公共安全方面具有很大的发展潜力,而且还可以直接用于活的生物体表面分析;大气压下的在线直接分析电离技术利用载气分子的激发态使得被分析化合物电离得到分子离子。针对不同的电离方法简单评述了其性能及应用,同时介绍了飞行时间质谱在串联方面的新发展,以及TOF-MS在仪器微型化方面的进展及其应用,并对飞行时间质谱仪今后的发展作了展望。     

Protein profiling for cancer biomarker discovery using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry and infrared imaging: a review

Cancer biomarker refers to a substance or process that is indicative of the presence of cancer in the body. A biomarker might be either a molecule secreted by a tumor or it can be a specific response of the body to the presence of cancer. Cancer biomarker-based diagnostics have applications for establishing disease predisposition, early detection, cancer staging, therapy selection, identifying whether or not a cancer is metastatic, therapy monitoring, assessing prognosis, and advances in the adjuvant setting. Full adoption of cancer biomarkers in the clinic has to date been slow, and only a limited number of cancer biomarker products are currently in routine use.Among proteomic technologies, matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF/MS) is a technique that has allowed rapid progress in cancer biology. Different further developed methods including e.g. SELDI (surface-enhanced laser desorption/ionization) and MELDI (material-enhanced laser desorption/ionization) are simple and high-throughput techniques that analyze with high sensitivity and specificity intact proteins expressed in complex biological mixtures, such as serum, urine, and tissues. The combination of mass spectrometry (MS) with infrared (IR) spectroscopic imaging is an attempt to combine different technologies in systems analytics. Both MALDI-TOF and infrared tissue imaging enable studying proteins distribution in tissue samples with a resolution down to 50 and 5 μm, respectively.In this review, we summarize recent applications and the synergistic combination of these new technologies to proteomic profiling for cancer biomarker discovery.     

De novo sequencing of novel neuropeptides directly from Ascaris suum tissue using matrix-assisted laser desorption/ionization time-of-flight/time-of-flight

Direct analysis of tissue by matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) allows for the rapid profiling of biological molecules with minimal loss of sample or degradation and reduced likelihood of chemical modification. However, there are still considerable challenges to overcome due to the complexity of tissue and the low quantity of endogenous peptide in a single cell. These problems are exacerbated in the nematode Ascaris suum because of the small size of individual neurons and the paucity of peptide per cell. In an effort to address these difficulties, the recently developed matrix-assisted laser desorption/ionization time-of-flight/time-of-flight (MALDI-TOF/TOF) technology was used in combination with an on-target derivatization in order to sequence novel neuropeptides directly from Ascaris nervous tissue. Direct MALDI-TOF/TOF analysis of Ascaris tissue provided the complete amino acid sequences for a previously characterized neuropeptide as well as for three novel peptides with homologues found in other nematodes. These results demonstrate a method for the rapid characterization of sub-femtomolar amounts of peptide directly from tissue using MALDI-TOF/TOF.     

空气动力辅助离子化质谱组织涂片分析用于胶质瘤异柠檬酸脱氢酶基因状态的快速判别

异柠檬酸脱氢酶(IDH)基因分型对于胶质瘤的精准诊疗具有重要意义。该文将组织涂片用于病理组织代谢物质谱分析的样品前处理,并采用2-羟基戊二酸与花生四烯酸质谱响应强度的比值作为胶质瘤IDH基因状态的判别指标,建立了基于空气动力辅助离子化(AFADESI)质谱技术的胶质瘤IDH基因状态快速判别分析方法。对组织涂片用于代谢物敞开式质谱分析的可行性进行考察和定量方法学验证,结果表明其具有样品分散性好、操作简单快速、代谢物覆盖度高、定量准确度好的优点。受试者工作曲线(ROC)评估显示,其用于胶质瘤IDH基因状态判别的诊断能力良好。组织涂片结合空气动力辅助离子化质谱分析用于胶质瘤IDH基因状态的快速判别有望为胶质瘤精准诊疗提供新的分析手段和技术支持。     

Interactive hyperspectral approach for exploring and interpreting DESI-MS images of cancerous and normal tissue sections

Desorption electrospray ionization (DESI) is an ambient mass spectrometry (MS) technique that can be operated in an imaging mode. It is known to provide valuable information on disease state and grade based on lipid profiles in tissue sections. Comprehensive exploration of the spatial and chemical information contained in 2D MS images requires further development of methods for data treatment and interpretation in conjunction with multivariate analysis. In this study, we employ an interactive approach based on principal component analysis (PCA) to interpret the chemical and spatial information obtained from MS imaging of human bladder, kidney, germ cell and prostate cancer and adjacent normal tissues. This multivariate strategy facilitated distinction between tumor and normal tissue by correlating the lipid information with pathological evaluation of the same samples. Some common lipid ions, such as those of m/z 885.5 and m/z 788.5, nominally PI(18 : 0/20 : 4) and PS(18 : 0/18 : 1), as well as ions of free fatty acids and their dimers, appeared to be highly characterizing for different types of human cancers, while other ions, such as those of m/z 465.5 (cholesterol sulfate) for prostate cancer tissue and m/z 795.5 (seminolipid 16 : 0/16 : 0) for germ tissue, appeared to be extremely selective for the type of tissue analyzed. These data confirm that lipid profiles can reflect not only the disease/health state of tissue but also are characteristic of tissue type. The manual interactive strategy presented here is particularly useful to visualize the information contained in hyperspectral MS images by automatically connecting regions of PCA score space to pixels of the 2D physical object. The procedures developed in this study consider all the spectral variables and their inter-correlations, and guide subsequent investigations of the mass spectra and single ion images to allow one to maximize characterization between different regions of any DESI-MS image.