On the development of plasma protein biomarkers

The development of plasma biomarkers has proven to be more challenging than initially anticipated. Many studies have reported lists of candidate proteins rather than validated candidate markers with an assigned performance to a specific clinical objective. Biomarker research necessitates a clear rational framework with requirements on a multitude of levels. On the technological front, the platform needs to be effective to detect low abundant plasma proteins and be able to measure them in a high throughput manner over a large amount of samples reproducibly. At a conceptual level, the choice of the technological platform and available samples should be part of an overall clinical study design that depends on a joint effort between basic and clinical research. Solutions to these needs are likely to facilitate more feasible studies. Targeted proteomic workflows based on SRM mass spectrometry show the potential of fast verification of biomarker candidates in plasma and thereby closing the gap between discovery and validation in the biomarker development pipeline. Biological samples need to be carefully chosen based on well-established guidelines either for candidate discovery in the form of disease models with optimal fidelity to human disease or for candidate evaluation as well-designed and annotated clinical cohort groups. Most importantly, they should be representative of the target population and directly address the investigated clinical question. A conceptual structure of a biomarker study can be provided in the form of several sequential phases, each having clear objectives and predefined goals. Furthermore, guidelines for reporting the outcome of biomarker studies are critical to adequately assess the quality of the research, interpretation and generalization of the results. By being attentive to and applying these considerations, biomarker research should become more efficient and lead to directly translatable biomarker candidates into clinical evaluation.     

DNA chips: the future of biomarkers

DNA chips are small, solid supports such as microscope slides onto which thousands of cDNAs or oligonucleotides are arrayed, representing known genes or simply EST clones, or covering the entire sequence of a gene with all its possible mutations. Fluorescently labeled DNA or RNA extracted from tissues is hybridized to the array. Laser scanning of the chip permits quantitative evaluation of each individual complementary sequence present in the sample. DNA chip technology is currently being proposed for qualitative and quantitative applications, firstly for the detection of point mutations, small deletions and insertions in genes involved in human diseases or affected during cancer progression; secondly, to determine on a genome-wide basis the pattern of gene expression in tumors, as well as in a number of experimental situations. The extraordinary power of DNA chips will have a strong impact on medicine in the near future, both in the molecular characterization of tumors and genetic diseases and in drug discovery and evaluation. Quantitative applications will soon spread through all fields of biology.     

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.     

Genetic biomarkers of depression

Depression is a term that has been used to describe a variety of ailments, ranging from minor to incapacitating. Clinically significant depression, termed as major depression, is a serious condition characterized not only by depressed mood but also by a cluster of somatic, cognitive, and motivational symptoms. Significant research efforts are aimed to understand the neurobiological as well as psychiatric disorders, and the evaluation of treatment of these disorders is still based solely on the assessment of symptoms. In order to identify the biological markers for depression, we have focused on gathering information on different factors responsible for depression including stress, genetic variations, neurotransmitters, and cytokines and chemokines previously suggested to be involved in the pathophysiology of depression. The present review illustrates the potential of biomarker profiling for psychiatric disorders, when conducted in large collections. The review highlighted the biomarker signatures for depression, warranting further investigation.     

神经胶质瘤生物标志物研究进展

神经胶质瘤(glioma)是最常见的原发性脑肿瘤,占颅内肿瘤的81%。神经胶质瘤的诊断手段与预后评估主要以影像学为主,但因神经胶质瘤的浸润性生长特点,影像学不能完全作为诊断及预后评估依据。因此,发现和鉴定全新生物标志物对神经胶质瘤的诊断、治疗和预后评估显得尤为重要。最新研究结果表明,在神经胶质瘤患者组织和血液中,多种生物标志物可用于神经胶质瘤的辅助诊断和预后评估。其中,诊断标志物包括IDH1/2基因突变、BRAF基因突变与融合、p53基因突变、端粒酶活性增加、循环肿瘤细胞和非编码RNA等。预后标志物包括1p/19p共缺失、MGMT基因启动子甲基化及基质金属蛋白酶-28、胰岛素样生长因子结合蛋白-2和CD26的表达上调和Smad4的表达下调。本文重点介绍了上述神经胶质瘤生物标志物在诊断和预后评估方面的最新研究进展。     

Potential biomarkers of ageing

Life span in individual humans is very heterogeneous.Thus, the ageing rate, measured as the decline of functional capacity and stress resistance, is different in every individual. There have been attempts made to analyse this individual age, the so-called biological age, in comparison to chronological age. Biomarkers of ageing should help to characterise this biological age and, as age is a major risk factor in many degenerative diseases,could be subsequently used to identify individuals at high risk of developing age-associated diseases or disabilities.Markers based on oxidative stress, protein glycation,inflammation, cellular senescence and hormonal deregulation are discussed.     

Discovery of urinary biomarkers

A myriad of proteins and peptides can be identified in normal human urine. These are derived from a variety of sources including glomerular filtration of blood plasma, cell sloughing, apoptosis, proteolytic cleavage of cell surface glycosylphosphatidylinositol-linked proteins, and secretion of exosomes by epithelial cells. Mass spectrometry-based approaches to urinary protein and peptide profiling can, in principle, reveal changes in excretion rates of specific proteins/peptides that can have predictive value in the clinical arena, e.g. in the early diagnosis of disease, in classification of disease with regard to likely therapeutic responses, in assessment of prognosis, and in monitoring response to therapy. These approaches have potential value, not only in diseases of the kidney and urinary tract but also in systemic diseases that are associated with circulating small protein and peptide markers that can pass the glomerular filter. Most large scale biomarker discovery studies reported thus far have used one of two approaches to identify proteins and peptides whose excretion in urine changes in specific disease states: 1) two-dimensional electrophoresis with mass spectrometric and/or immunochemical identification of proteins and 2) top-down mass spectrometric methods (SELDI-TOF-MS and capillary electrophoresis-MS). These studies have been chiefly in the areas of nephrology, urology, and oncology. We review these applications, focusing on two areas of progress, viz. in bladder cancer and in acute rejection of renal transplants. Progress has been limited so far. However, with the advent of powerful LC-MS/MS methods along with methods for quantifying LC-MS/MS output, there is hope for an accelerated discovery and validation of disease biomarkers in urine.     

Immunological biomarkers of tuberculosis

Currently there are no sufficiently validated biomarkers to aid the evaluation of new tuberculosis vaccine candidates, the improvement of tuberculosis diagnostics or the development of more effective and shorter treatment regimens. To date, the detection of Mycobacterium tuberculosis or its products has not been able to adequately address these needs. Understanding the interplay between the host immune system and M. tuberculosis may provide a platform for the identification of suitable biomarkers, through both unbiased and targeted hypothesis-driven approaches. Here, we review immunological markers, their relation to M. tuberculosis infection stages and their potential use in the fight against tuberculosis.     

子宫颈癌细胞学新型生物标志、诊断标志物的筛选和开发现状

子宫颈癌至今仍是全球范围内一个重要的公共卫生问题，是妇女疾病死亡的主要原因之一。因此，子宫颈癌细胞学的筛查、早期诊断和治疗越来越受到重视，虽然新的技术不断推出使子宫颈癌的早期筛查及诊治水平有了很大提高，但仍缺乏新型的特异性生物学标志物。本文从新的子宫颈癌相关蛋白生物标志物和诊断靶标的发现，治疗子宫颈癌的药物作用、治疗靶标和作用机制的评估，子宫颈癌相关微小核糖核酸作为诊断和治疗靶标的筛选等方面对子宫颈脱落细胞筛查方法的开发和研究进展进行综述，为子宫颈癌的早期筛查和诊断寻找新的生物学标志物。     

Monitoring of mycotoxin biomarkers in the Czech Republic

AFM₁ was determined in 72 (72%) samples of human urine, range 19-6064 pg/g creatinine, mean 367 pg/g creatinine, median 158 pg/g creatinine and 90% percentile 755 pg/g creatinine in 1997. AFM₁ was determined in 46 (43.8%) samples of human urine, range 21-19219 pg/g creatinine, mean 414 pg/g creatinine, median 96 pg/g creatinine and 90% percentile 415 pg/g creatinine in 1998. OTA was determined in 2077 (94.2%) samples of human serum, range 0.1–13.7 μg/L, mean 0.28 μg/L, median 0.2 μg/L and 90% percentile 0.5 μg/L in 1994–2002. OTA was determined in 12 (40%) samples of human kidneys, range 0.1–0.2 μg/kg, mean 0.07 μg/kg, and median 0.05 μg/kg in 2001. Presented at the 26^th Mykotoxin-Workshop in Herrsching, Germany, May 17–19, 2004.     

药物类过敏反应生物标志物探究

药物类过敏反应为非免疫球蛋白E(IgE)介导的急性过敏反应,与Ⅰ型超敏反应临床症状相似,首次接触药物即可发生,在临床药物过敏反应中占有相当大的比例.药物类过敏反应生物标志物可特异性反映药物类过敏反应的发生发展,监测其生物标志物可实现对该不良反应进行可靠的非临床评价和临床诊断,从而降低该不良反应的发生率.本文介绍了药物类过敏反应特点,重点阐述了组胺等几种药物类过敏反应生物标志物的研究现状,希望为药物类过敏反应的非临床评价以及临床诊断提供参考.     

Assessing the predictive power of newly added biomarkers

As medical research and technology advance, there are always new biomarkers found and predictive models proposed for improving the diagnostic performance of diseases. Therefore, in addition to the existing biomarkers and predictive models, how to assess new biomarkers becomes an important research problem. Many classification performance measures, which are usually based on the performance on the whole cut‐off values, were applied directly to this type of problems. However, in a medical diagnosis, some cut‐off points are more important, such as those points within the range of high specificity. Thus, as the partial area under the ROC curve to the area under ROC curve, we study the partial integrated discriminant improvement (pIDI) for evaluating the predictive ability of a newly added marker at a prespecified range of cut‐offs. Theoretical property of estimate of the proposed measure is reported. The performance of this new measure is then compared with that of the partial area under an ROC curve. The numerical results use synthesized are presented, and a liver cancer dataset is used for demonstration purposes.     

Methods for the absolute quantification of N-glycan biomarkers

BackgroundMany treatment options especially for cancer show a low efficacy for the majority of patients demanding improved biomarker panels for patient stratification. Changes in glycosylation are a hallmark of many cancers and inflammatory diseases and show great potential as clinical disease markers. The large inter-subject variability in glycosylation due to hereditary and environmental factors can complicate rapid transfer of glycan markers into the clinical practice but also presents an opportunity for personalized medicine.Scope of reviewThis review discusses opportunities of glycan biomarkers in personalized medicine and reviews the methodology for N-glycan analysis with a specific focus on methods for absolute quantification.Major conclusionsThe entry into the clinical practice of glycan markers is delayed in large part due to a lack of adequate methodology for the precise and robust quantification of protein glycosylation. Only absolute glycan quantification can provide a complete picture of the disease related changes and will provide the method robustness required by clinical applications.General significanceGlycan biomarkers have a huge potential as disease markers for personalized medicine. The use of stable isotope labeled glycans as internal standards and heavy-isotope labeling methods will provide the necessary method precision and robustness acceptable for clinical use. This article is part of a Special Issue entitled “Glycans in personalized medicine” Guest Editor: Professor Gordan Lauc.     

So, you want to look for biomarkers (introduction to the special biomarkers issue)

The burgeoning field of proteomics plays a powerful and relevant role in the discovery of biomarkers, which are biometric measurements that convey information about the biological condition of the subject being tested. Biomarkers have changed the manner in which we diagnose disease, monitor the effect of therapy, classify disease, detect toxicity, and develop new drugs. The central part that proteins command in both disease etiology and treatment make them prime biomarker candidates. Indeed, the majority of clinical tests in use today measure proteins. This perspective introduces the Journal of Proteome Research Special Issue on Proteomics and Biomarkers. It outlines the major applications of biomarkers, discusses the basics of statistically assessing them and considers the crucial choice of sample type. Central considerations of biomarker discovery and validation, particularly with respect to their intended clinical and research applications, are highlighted.     

污染土壤的生物标记物研究进展

生物标记物是指示环境中污染物危害效应的生物信号。利用生物标记物进行污染土壤的检测和定量分析是最可行的方法之一。本文主要综述了近年来一些典型的、指示土壤污染的几类生物标记物 (如细胞色素P4 5 0加氧酶系统、细胞抗氧化酶及DNA指纹技术 )的最新研究进展 ,并探讨了生物标记物在污染土壤修复效果评价及其早期诊断方面的应用前景。