High-throughput intracellular pteridinic profiling by liquid chromatography–quadrupole time-of-flight mass spectrometry

Pteridines are a diverse family of endogenous metabolites that may serve as useful diagnostic biomarkers for disease. While many preparative and analytical techniques have been described for analysis of selected pteridines in biological fluids, broad intracellular pteridine detection remains a significant analytical challenge. In this study, a novel, specific and sensitive extraction and high performance liquid chromatography–quadrupole time-of-flight mass spectrometry (HPLC–QTOF MS) method was developed to simultaneously quantify seven intracellular pteridines and monitor 18 additional, naturally-occurring intracellular pteridines. The newly developed method was validated through evaluation of spiked recoveries (84.5–109.4%), reproducibility (2.1–5.4% RSD), method detection limits (0.1–3.0 μg L⁻¹) and limits of quantitation (0.1–1 μg L⁻¹), and finally application to non-small cell lung cancer A549 cells. Twenty-three pteridine derivatives were successfully detected from cell lysates with an average RSD of 12% among culture replicates. Quantified intracellular pteridine levels ranged from 1 to 1000 nM in good agreement with previous studies. Finally, this technique may be applied to cellular studies to generate new biological hypotheses concerning pteridine physiological and pathological functions as well as to discovery new pteridine-based biomarkers.     

Recent developments in the determination of urinary cancer biomarkers by capillary electrophoresis

Investigation of effective biomarkers for cancers is currently a popular area of study in clinical and cancer researches, because it can potentially lead to pre-cancer screening or pre-cancer diagnosis and may provide useful information on cancer type and the disease's stage of progression. More and more biochemical or chemical fluid components of the human body such as urine, blood, and cerebrospinal fluid have been considered to contain biomarkers, which are useful in cancer researches, pre-cancer diagnosis, and cancer follow-ups during or after cancer treatment. Several modern analytical techniques, such as gas chromatography (GC), high-performance liquid chromatography (HPLC), capillary electrophoresis (CE), and other separation techniques as well as hyphenated techniques, have been extensively used in study of cancer biomarkers. Among these techniques, CE is considered to be a highly efficient and practical analytical technique because of the small sample volume requirement and its wide separation versatility, ranging from small inorganic molecules to large biomolecules. This review discusses the latest developments involving biomarkers and their analysis by CE, including a discussion of instrumental conditions, method developments, and data analysis.     

Metabolomics: a revolution for novel cancer marker identification

The repertoire of small-molecular-weight substances present in cells, tissue and body fluids are known as the metabolites. The global analysis of metabolites, such as by high-resolution 1H nuclear magnetic resonance spectroscopy and mass spectrometry, is integral to the rapidly expanding field of metabolomics, which is making progress in various diseases. In the area of cancer and metabolic phenotype, the integrated analysis of metabolites may provide a powerful platform for detecting changes related to cancer diagnosis and discovering novel biomarkers. In this review, metabolomics including the technologies in metabolomics research and extracting information from metabolomics datasets are described. Then we discuss the challenges and opportunities in metabolomics for finding metabolic processes in cancer and discovering novel cancer biomarkers. Finally, we assess the clinical applicability of metabolomics.     

Application of capillary electrophoresis for the early diagnosis of cancer

Early diagnosis is the key to the effective treatment of cancer. The detection of cancer biomarkers plays a critical role not only in cancer early diagnosis, but also in classification and staging tumor progression, or assessment prognosis and treatment response. Currently, various molecular diagnostic techniques have been developed for cancer biomarker studies, with many of the more effective approaches requiring a separation step before detection. Capillary electrophoresis (CE) can perform rapid and efficient separation with small samples, which is well-suited for analysis of both small- and macro- molecule biomarkers in complex samples. CE has different separation modes and can couple to different detectors into a variety of platforms, such as conducting studies on DNA/ RNA point mutation, protein misexpression, and metabolite abnormality. Similarly, microchip capillary electrophoresis (MCE) appears as a very important biomarker screening platform with the merits of high throughput, integration, and miniaturization, which makes it a promising clinical tool. By hyphenated different detectors, or integrated with immunoassay, PCR/LDR and related technologies, MCE can be constructed into diverse platforms used in genomics, proteomics, and metabolomics study for biomarkers discovery. The multiplex biomarker screening approach via CE- or MCE-based platforms is becoming a trend. This paper focuses on studies of cancer biomarkers via CE/MCE platforms, based on the studies published over the past 3 years. Some recent CE applications in the field of cancer study, such as cancer theranostics, are introduced.     

Identifying potential serum biomarkers of breast cancer through targeted free fatty acid profiles screening based on a GC–MS platform

Recent advances suggest that abnormal fatty acid metabolism highly correlates with breast cancer, which provide clues to discover potential biomarkers of breast cancer. This study aims to identify serum free fatty acid (FFA) metabolic profiles and screen potential biomarkers for breast cancer diagnosis. Gas chromatography–mass spectrometry and our in-house fatty acid methyl ester standard substances library were combined to accurately identify FFA profiles in serum samples of breast cancer patients and breast adenosis patients (as controls). Potential biomarkers were screened by applying statistical analysis. A total of 18 FFAs were accurately identified in serum sample. Two groups of patients were correctly discriminated by the orthogonal partial least squares–discriminant analysis model based on FFA profiles. Seven FFA levels were significantly higher in serum from breast cancer patients than that in controls, and exhibited positive correlation with malignant degrees of disease. Furthermore, five candidates (palmitic acid, oleic acid, cis-8,11,14-eicosatrienoic acid, docosanoic acid and the ratio of oleic acid to stearic acid) were selected as potential serum biomarkers for differential diagnosis of breast cancer. Our study will help to reveal the metabolic signature of FFAs in breast cancer patients, and provides valuable information for facilitating clinical noninvasive diagnosis.     

Sparse optimal scoring for multiclass cancer diagnosis and biomarker detection using microarray data

Gene expression data sets hold the promise to provide cancer diagnosis on the molecular level. However, using all the gene profiles for diagnosis may be suboptimal. Detection of the molecular signatures not only reduces the number of genes needed for discrimination purposes, but may elucidate the roles they play in the biological processes. Therefore, a central part of diagnosis is to detect a small set of tumor biomarkers which can be used for accurate multiclass cancer classification. This task calls for effective multiclass classifiers with built-in biomarker selection mechanism. We propose the sparse optimal scoring (SOS) method for multiclass cancer characterization. SOS is a simple prototype classifier based on linear discriminant analysis, in which predictive biomarkers can be automatically determined together with accurate classification. Thus, SOS differentiates itself from many other commonly used classifiers, where gene preselection must be applied before classification. We obtain satisfactory performance while applying SOS to several public data sets.     

Electrochemical Biosensing in Cancer Diagnostics and Follow‐up

In cancer, screening and early detection are critical for the success of the patient's treatment and to increase the survival rate. The development of analytical tools for non‐invasive detection, through the analysis of cancer biomarkers, is imperative for disease diagnosis, treatment and follow‐up. Tumour biomarkers refer to substances or processes that, in clinical settings, are indicative of the presence of cancer in the body. These biomarkers can be detected using biosensors, that, because of their fast, accurate and point of care applicability, are prominent alternatives to the traditional methods. Moreover, the constant innovations in the biosensing field improve the determination of normal and/or elevated levels of tumour biomarkers in patients’ biological fluids (such as serum, plasma, whole blood, urine, etc.). Although several biomarkers (DNA, RNA, proteins, cells) are known, the detection of proteins and circulating tumour cells (CTCs) are the most commonly reported due to their approval as tumour biomarkers by the specialized entities and commonly accepted for diagnosis by medical and clinical teams. Therefore, electrochemical immunosensors and cytosensors are vastly described in this review, because of their fast, simple and accurate detection, the low sample volumes required, and the excellent limits of detection obtained. The biosensing strategies reported for the six most commonly diagnosed cancers (lung, breast, colorectal, prostate, liver and stomach) are summarized and the distinct phases of the sensors’ constructions (surface modification, antibody immobilization, immunochemical interactions, detection approach) and applications are discussed.     

毛细管电泳-激光诱导荧光检测法分析胃癌组织及癌旁正常组织蛋白质的差异性

胃癌是临床常见的恶性肿瘤之一。近年来寻找肿瘤相关特异蛋白质是蛋白质组学研究的热点。本文通过考察毛细管动态涂层方法、筛分介质聚环氧乙烷(PEO)的浓度、缓冲液的pH值、分离电压、温度及荧光染料对分离效果的影响,建立了毛细管电泳-激光诱导荧光法分离胃癌组织及癌旁正常组织蛋白质的方法;通过分离检测,获得两者的蛋白质指纹图谱。经分析,两者的指纹图谱相似度达到0.8以上,差异蛋白质分子质量集中在50000~100000 Da之间,提示某些小分子蛋白质可能是和肿瘤发生相关的特异蛋白质,从而缩小了特异性分子标记物的筛选范围。病理组织学分型及蛋白质电泳峰数目的统计结果验证了该方法的可靠性。该方法具有临床应用的潜力。     

Plasmonic Gold Chip for Multiplexed Detection of Ovarian Cancer Biomarker in Urine

Human epididymal protein 4(HE4), carbohydrate antigen 125 (CA125) and osteopontin(OPN) are three key biomarkers in detecting ovarian cancer. To explore the diagnosis value of combined detection of these three biomarkers for ovarian cancer, we developed a multiplexed assay on a plasmonic gold(pGOLD) platform for measuring HE4, CA125 and OPN in urine. The receiver operator characteristic(ROC) curve was drawn, and the diagnosis values of each biomarker alone or in combination for ovarian cancer were evaluated. In the analysis to distinguish ovarian cancer from other gynecological cancers, ovarian cysts and healthy people, the sensitivities of HE4, CA125 and OPN were 72.55%, 52.82% and 68.63%, the specificity values were 95.06%, 87.65% and 90.12%, while the areas under the curve(AUC) were 0.85, 0.75 and 0.77, respectively. The sensitivity and specificity for combination detection of the three markers were 90.20% and 80.25%. The detection methods of HE4, CA125 and OPN based on plasma fluorescence enhanced chip showed good analytic and diagnostic performance, and provided a non-invasive method for the diagnosis of ovarian cancer.     

Use of quantum dots in the development of assays for cancer biomarkers

Biomarker assays may be useful for screening and diagnosis of cancer if a set of molecular markers can be quantified and statistically differentiated between cancerous cells and healthy cells. Markers of disease are often present at very low concentrations, so methods capable of low detection limits are required. Quantum dots (QDs) are nanoparticles that are emerging as promising probes for ultrasensitive detection of cancer biomarkers. QDs attached to antibodies, aptamers, oligonucleotides, or peptides can be used to target cancer markers. Their fluorescent properties have enabled QDs to be used as labels for in-vitro assays to quantify biomarkers, and they have been investigated as in-vivo imaging agents. QDs can be used as donors in assays involving fluorescence resonance energy transfer (FRET), or as acceptors in bioluminescence resonance energy transfer (BRET). The nanoparticles are also capable of electrochemical detection and are potentially useful for “lab-on-a-chip” applications. Recent developments in silicon QDs, non-blinking QDs, and QDs with reduced-size and controlled-valence further make these QDs bioanalytically attractive because of their low toxicity, biocompatibility, high quantum yields, and diverse surface modification flexibility. The potential of multiplexed sensing using QDs with different wavelengths of emission is promising for simultaneous detection of multiple biomarkers of disease.

Multiplexed detection of serological cancer markers with plasmon-enhanced Raman spectro-immunoassay

Circulating biomarkers have emerged as promising non-invasive, real-time surrogates for cancer diagnosis, prognostication and monitoring of therapeutic response. Emerging data, however, suggest that single markers are inadequate in describing complex pathologic transformations. Architecting assays capable of parallel measurements of multiple biomarkers can help achieve the desired clinical sensitivity and specificity while conserving patient specimen and reducing turn-around time. Here we describe a plasmon-enhanced Raman spectroscopic assay featuring nanostructured biomolecular probes and spectroscopic imaging for multiplexed detection of disseminated breast cancer markers cancer antigen (CA) 15-3, CA 27-29 and cancer embryonic antigen (CEA). In the developed SERS assay, both the assay chip and surface-enhanced Raman spectroscopy (SERS) tags are functionalized with monoclonal antibodies against CA15-3, CA27-29 and CEA, respectively. Sequential addition of biomarkers and functionalized SERS tags onto the functionalized assay chip enable the specific recognition of these biomarkers through the antibody-antigen interactions, leading to a sandwich spectro-immunoassay. In addition to offering extensive multiplexing capability, our method provides higher sensitivity than conventional immunoassays and demonstrates exquisite specificity owing to selective formation of conjugated complexes and fingerprint spectra of the Raman reporter. We envision that clinical translation of this assay may further enable asymptomatic surveillance of cancer survivors and speedy assessment of treatment benefit through a simple blood test.     

Design of high stability thin-film transistor biosensor for the diagnosis of bladder cancer

Bladder cancer is the most common malignant tumor in the urinary system,with high morbidity,mortality and recurrence after surgery.However,current bladder cancer urine diagnosis methods are limited by the low accuracy and specificity due to the low abundance of bladder cancer biomarkers in the urine with complex biological environments.Herein,we present a high stability indium gallium zinc oxide field effect transistor(IGZO-FET) biosensor for efficient identification of bladder cancer biomarkers from human urine samples.The recognition molecular functionalized IGZO-FET biosensor exhibits stable electronic and sensing performance due to the large-area fabrication of IGZO thin-film FET.Owing to the excellent electrical performance of IGZO-FET,the IGZO-FET biosensor exhibits high sensitivity and extremely low detection limit(2.7 amol/L) towards bladder cancer biomarkers.The IGZO-FET biosensor is also able to directly detect bladder tumor biomarker in human urine with high sensitivity and specificity,and could differentiate bladder cancer patients' urine samples from healthy donors effectively.These results indicate that our designed high-performance biosensor shows great potential in the application of portable digital bladder cancer diagnosis devices.     

Molecularly imprinted polymers outperform lectin counterparts and enable more precise cancer diagnosis

Accurately analysing the particular glycosylation status of protein biomarkers is of significant importance in the precise, early diagnosis of cancer. Existing methods mainly rely on the use of antibodies and lectins. However, due to the macroscopic and microscopic heterogeneity of glycans, precise analysis of glycosylation status still remains a challenge. Molecularly imprinted polymers (MIPs), as a synthetic alternative to antibodies or lectins, may provide new solutions but have not yet been explored. Herein, we report an appealing strategy called triple MIP-based plasmonic immunosandwich assay (triMIP-PISA) for precise cancer diagnosis in terms of the relative glycosylation expression of glycoprotein biomarkers. As proof of the principle, alpha fetoprotein (AFP), which has been used as a clinical biomarker for early detection of hepatocellular carcinoma (HCC), as well as its Lens culinaris agglutinin (LCA)-reactive fraction (AFP-L3), which is mainly composed of core-fucosylated glycans, were used as two target proteoforms to test in this study. Using two MIPs that can specifically recognize the peptide sequence of AFP as well as a fucose-imprinted MIP that can specifically recognize the AFP-L3 fraction, facile simultaneous plasmon-enhanced Raman detection of AFP and AFP-L3 in serum was achieved, which allowed HCC patients to be distinguished from healthy individuals. Due to the excellent recognition properties of the MIPs that are comparable to those of antibodies and superior to those of lectins, our triMIP-PISA method exhibited improved precision as compared with an antibody plus lectin-based immunofluorescence assay. Thus, this strategy opened a new avenue towards the precise diagnosis of cancer.

A triple molecularly imprinted polymer (MIP)-based plasmonic assay was developed for precise cancer diagnosis in terms of the relative glycosylation expression of glycoprotein biomarkers.     

Cell-based sensor for analysis of EGFR biomarker expression in oral cancer

Oral cancer is the sixth most common cancer worldwide and has been marked by high morbidity and poor survival rates that have changed little over the past few decades. Beyond prevention, early detection is the most crucial determinant for successful treatment and survival of cancer. Yet current methodologies for cancer diagnosis based upon pathological examination alone are insufficient for detecting early tumor progression and molecular transformation. To address this clinical need, we have developed a cell-based sensor to detect oral cancer biomarkers, such as the epidermal growth factor receptor (EGFR) whose over-expression is associated with early oral tumorigenesis and aggressive cancer phenotypes. The lab-on-a-chip (LOC) sensor utilizes an embedded track-etched membrane, which functions as a micro-sieve, to capture and enrich cells from complex biological fluids or biopsy suspensions. Once captured, "on-membrane" immunofluorescent assays reveal the presence and isotype of interrogated cells via automated microscopy and fluorescent image analysis. Using the LOC sensor system, with integrated capture and staining technique, EGFR assays were completed in less than 10 minutes with staining intensity, homogeneity, and cellular localization patterns comparable to conventional labeling methods. Further examination of EGFR expression in three oral cancer cell lines revealed a significant increase (p < 0.05) above control cells with EGFR expression similar to normal squamous epithelium. Results obtained in the microfluidic sensor system correlated well with flow cytometry (r(2) = 0.98), the "gold standard" in quantitative protein expression analysis. In addition, the LOC sensor detected significant differences between two of the oral cancer cell lines (p < 0.01), accounting for disparity of approximately 34 000 EGFR per cell according to quantitative flow cytometry. Taken together, these results support the LOC sensor system as a suitable platform for rapid detection of oral cancer biomarkers and characterization of EGFR over-expression in oral malignancies. Application of this technique may be clinically useful in cancer diagnostics for early detection, prognostic evaluation, and therapeutic selection. Having demonstrated the functionality of this integrated microfluidic sensor system, further studies using clinical samples from oral cancer patients are now warranted.     

膀胱癌液体活检的研究进展

膀胱癌是一种高发病率和致死率的恶性肿瘤疾病,通常情况下在中后期才能被诊断出来,给患者带来了巨大的身心伤害。 膀胱镜检查是膀胱癌诊断的金标准,但这种方法具有一定的侵入性,并且在膀胱癌的早期诊断中,灵敏度和特异性较低,容易出现较高的假阳性率。 膀胱癌的发生会对血液和尿液的成分产生直接影响,因此非侵入性的液体活检将为膀胱癌的早期诊断带来新的检测方法。 本篇综述介绍了基于液体活检的膀胱癌诊断方法的发展进程。 首先,对膀胱癌的主要标志物进行了简单介绍。 其次,重点总结了以液体(如尿液和血液)为检测对象的膀胱癌诊断方法和诊断机制。 除此之外,我们对膀胱癌液体活检面临的机遇和挑战进行了阐述。 我们希望这篇综述将为膀胱癌的液体活检提供指导。     

Construction of high stability indium gallium zinc oxide transistor biosensors for reliable detection of bladder cancer-associated microRNA

Bladder cancer is the most common malignant tumours with high morbidity, mortality and recurrence.However, currently developed detection methods for bladder cancer-associated urine biomarkers are hindered by their extremely low abundance. Hence, the exploration of a highly sensitive and selective approach for the detection of trace bladder cancer-associated biomarkers in human urine is of vital importance for the diagnosis of bladder cancer. Herein, we developed a highly reliable indium gallium ...     

A proteomic approach to investigate potential biomarkers directed against membrane-associated breast cancer proteins

The identification of specific protein markers for breast cancer would provide the basis for early diagnosis. Particularly, membrane and membrane-associated proteins are rich in targets for antibodies that may constitute suitable biomarkers of carcinogenesis. However, membrane proteins separation using 2-DE remains difficult. In this work, the breast cancer cell line MCF7 was used as source of proteins for the screening of potential cell membrane-associated antigens recognized by autoantibodies in patients with breast cancer and healthy volunteers. The protein extract obtained using trifluoroethanol (TFE) as cosolvent was compared to a total cell lysate protein extract prepared by a current technique. After 2-DE separation of the two extracts, their protein patterns clearly differed. About 63% of the proteins identified in the TFE-extract were predicted to possess at least one transmembrane domain. 2-D blots probed with sera from cancer patients or from healthy volunteers showed that, as expected, additional antigens were provided in the TFE-extract. Thus, the method described here appeared well suited for proteomic investigation of potential biomarkers undetected by current techniques.     

Determination of Carcinoembryonic Antigen by Surface-Enhanced Raman Spectroscopy Using Gold Nanobowl Arrays

Surface-enhanced Raman scattering (SERS) based on the double-antibody sandwich format is reported for the determination of carcinoembryonic antigen. Ordered gold nanobowl arrays were fabricated and conjugated with anticarcinoembryonic as capturing substrates, and gold nanoshells, adsorbed with 4-mercaptobenzonic acid, were modified with anticarcinoembryonic antigen as labeling tags. After the carcinoembryonic antigen was captured on ordered gold nanobowl arrays, the labeling tags were bonded to the captured carcinoembryonic antigen. The interaction of SERS substrates (ordered gold nanobowl arrays) and SERS labels (gold nanoshells) showed high sensitivity and a low detection limit for carcinoembryonic antigen. The linear dynamic range of SERS for carcinoembryonic antigen was from 5?pg/mL to 100?ng/mL with a linear relationship between carcinoembryonic antigen concentration and SERS intensity. The detection limit was 1.73?pg/mL. SERS detection may be used for other cancer biomarkers and provides potential for the clinical diagnosis of cancer biomarkers.     

Proteomics analysis of human breast milk by two-dimensional polyacrylamide gel electrophoresis (2D-PAGE) coupled with mass spectrometry to assess breast cancer risk

Breast cancer (BC) is one of the most common cancers and one of the most common causes for cancer-related mortality. Discovery of protein biomarkers associated with cancer is considered important for early diagnosis and prediction of the cancer risk. Protein biomarkers could be investigated by large-scale protein investigation or proteomics, using mass spectrometry (MS)-based techniques. Our group applies MS-based proteomics to study the protein pattern in human breast milk from women with BC and controls and investigates the alterations and dysregulations of breast milk proteins in comparison pairs of BC versus control. These dysregulated proteins might be considered potential future biomarkers of BC. Identification of potential biomarkers in breast milk may benefit young women without BC, but who could collect the milk for future assessment of BC risk. Previously we identified several dysregulated proteins in different sets of human breast milk samples from BC patients and controls using gel-based protein separation coupled with MS. Here, we performed 2D-PAGE coupled with nano-liquid chromatography–tandem MS (nanoLC-MS/MS) in a small-scale study on a set of six human breast milk pairs (three BC samples vs. three controls) and we identified several dysregulated proteins that have potential roles in cancer progression and might be considered potential BC biomarkers in the future.     

Bioanalytical methods for metabolomic profiling: Detection of head and neck cancer,including oral cancer

Metabolomics is an emerging field dealing with the measurement and interpretation of small molecular byproducts of biochemical processes, or metabolites, which can be used to generate profiles from biological samples. Promising for use in pathophysiology, metabolomic profiles give the immediate biological state of a sample. These profiles are altered in diseases and are detectable in biological samples, such as tissue, blood, urine, saliva, and others. Most remarkably, metabolic profiles usually are altered before symptoms appear in a patient. For this reason, metabolomics has potential as a reliable method for an early diagnosis of diseases through disease biomarker identification. This application is most prevalent in cancer, such as head and neck cancer (HNC). Metabolomic studies offer avenues to improve on current medical techniques through the application of mass spectrometry (MS), nuclear magnetic resonance spectroscopy (NMR), and statistical analysis to determine better biomarkers than those currently known. In this review, we discuss the use of MS and NMR tools for detecting biomarkers in tissue and fluid samples, and the appropriateness of metabolomics in analyzing cancer. Advantages, disadvantages, and recent studies on metabolomic profiling techniques in HNC analysis are also discussed herein.