Development of biosensors for cancer clinical testing

Biosensors are devices that combine a biochemical recognition/binding element (ligand) with a signal conversion unit (transducer). Biosensors are already used for several clinical applications, for example for electrochemical measurement of blood glucose concentrations. Application of biosensors in cancer clinical testing has several potential advantages over other clinical analysis methods including increased assay speed and flexibility, capability for multi-target analyses, automation, reduced costs of diagnostic testing and a potential to bring molecular diagnostic assays to community health care systems and to underserved populations. They have the potential for facilitating Point of Care Testing (POCT), where state-of-the-art molecular analysis is carried out without requiring a state-of-the-art laboratory. However, not many biosensors have been developed for cancer-related testing. One major challenge in harnessing the potential of biosensors is that cancer is a very complex set of diseases. Tumors vary widely in etiology and pathogenesis. Oncologists rely heavily on histological characterization of tumors and a few biomarkers that have demonstrated clinical utility to aid in patient management decisions. New genomic and proteomic molecular tools are being used to profile tumors and produce "molecular signatures." These signatures include genetic and epigenetic signatures, changes in gene expression, protein profiles and post-translational modifications of proteins. These molecular signatures provide new opportunities for utilizing biosensors. Biosensors have enormous potential to deliver the promise of new molecular diagnostic strategies to patients. This article describes some of the basic elements of cancer biology and cancer biomarkers relevant for the development of biosensors for cancer clinical testing, along with the challenges in using this approach.     

Ethical and legal aspects of oncogenomics

The discovery of the genes and cellular pathways that play fundamental roles in several diseases, and the understanding of many diseases at a molecular level due to the advances in the field of genomics, have revolutionized the diagnosis, therapy and prevention of human diseases. Application of genetic testing in numerous medical fields, including pharmacogenomics and oncogenomics, raised numerous ethical questions and introduced legal instruments that are aimed at ensuring the appropriate protection of human research participants. For the effective development of human genomics and translation of novel, validated biomarkers into potentially useful clinical applications in personalized medicine, there is a need for clear ethical standards and principles in all phases of clinical research.     

Proteomics in reproductive biology: Beacon for unraveling the molecular complexities

Proteomics, an interface of rapidly evolving advances in physics and biology, is rapidly developing and expanding its potential applications to molecular and cellular biology. Application of proteomics tools has contributed towards identification of relevant protein biomarkers that can potentially change the strategies for early diagnosis and treatment of several diseases. The emergence of powerful mass spectrometry-based proteomics technique has added a new dimension to the field of medical research in liver, heart diseases and certain forms of cancer. Most proteomics tools are also being used to study physiological and pathological events related to reproductive biology. There have been attempts to generate the proteomes of testes, sperm, seminal fluid, epididymis, oocyte, and endometrium from reproductive disease patients. Here, we have reviewed proteomics based investigations in humans over the last decade, which focus on delineating the mechanism underlying various reproductive events such as spermatogenesis, oogenesis, endometriosis, polycystic ovary syndrome, embryo development. The challenge is to harness new technologies like 2-DE, DIGE, MALDI-MS, SELDI-MS, MUDPIT, LC–MS etc., to a greater extent to develop widely applicable clinical tools in understanding molecular aspects of reproduction both in health and disease.     

Semiconductor quantum dots for in vitro diagnostics and cellular imaging

The need for companion diagnostics, point-of-care testing (POCT) and high-throughput screening in clinical diagnostics and personalized medicine has pushed the need for more biological information from a single sample at extremely low concentrations and volumes. Optical biosensors based on semiconductor quantum dots (QDs) can answer these requirements because their unique photophysical properties are ideally suited for highly sensitive multiplexed detection. Many different biological systems have been successfully scrutinized with a large variety of QDs over the past decade but their future as widely applied commercial biosensors is still open. In this review, we highlight recent in vitro diagnostic and cellular imaging applications of QDs and discuss milestones and obstacles on their way toward integration into real-life diagnostic and medical applications.     

生物芯片、生物传感器和生物信息学

近年来,在生物技术和医学研究领域涌现出了许多新技术平台,其中就包括生物芯片技术和生物传感器技术。生物芯片和生物传感器的构建都必须以生物信息学为基础,而两种技术平台应用所得出的数据和结果又反过来大大丰富和充实了生物信息学本身。本分析概述了生物芯片和生物传感器两种技术平台以及生物信息学,对三之间的相互关系进行了讨论。     

Proteomics in clinical trials and practice: present uses and future promise

The study of clinical proteomics is a promising new field that has the potential to have many applications, including the identification of biomarkers and monitoring of disease, especially in the field of oncology. Expression proteomics evaluates the cellular production of proteins encoded by a particular gene and exploits the differential expression and post-translational modifications of proteins between healthy and diseased states. These biomarkers may be applied towards early diagnosis, prognosis, and prediction of response to therapy. Functional proteomics seeks to decipher protein-protein interactions and biochemical pathways involved in disease biology and targeted by newer molecular therapeutics. Advanced spectrometry technologies and new protein array formats have improved these analyses and are now being applied prospectively in clinical trials. Further advancement of proteomics technology could usher in an era of personalized molecular medicine, where diseases are diagnosed at earlier stages and where therapies are more effective because they are tailored to the protein expression of a patient's malignancy.     

geneCBR: a translational tool for multiple-microarray analysis and integrative information retrieval for aiding diagnosis in cancer research

Background  

Bioinformatics and medical informatics are two research fields that serve the needs of different but related communities. Both domains share the common goal of providing new algorithms, methods and technological solutions to biomedical research, and contributing to the treatment and cure of diseases. Although different microarray techniques have been successfully used to investigate useful information for cancer diagnosis at the gene expression level, the true integration of existing methods into day-to-day clinical practice is still a long way off. Within this context, case-based reasoning emerges as a suitable paradigm specially intended for the development of biomedical informatics applications and decision support systems, given the support and collaboration involved in such a translational development. With the goals of removing barriers against multi-disciplinary collaboration and facilitating the dissemination and transfer of knowledge to real practice, case-based reasoning systems have the potential to be applied to translational research mainly because their computational reasoning paradigm is similar to the way clinicians gather, analyze and process information in their own practice of clinical medicine.     

Serum biomarkers in interstitial lung diseases

The use of biomarkers in medicine lies in their ability to detect disease and support diagnostic and therapeutic decisions. New research and novel understanding of the molecular basis of the disease reveals an abundance of exciting new biomarkers who present a promise for use in the everyday clinical practice. The past fifteen years have seen the emergence of numerous clinical applications of several new molecules as biologic markers in the research field relevant to interstitial lung diseases (translational research). The scope of this review is to summarize the current state of knowledge about serum biomarkers in interstitial lung diseases and their potential value as prognostic and diagnostic tools and present some of the future perspectives and challenges.     

数字聚合酶链反应及其在感染性疾病中的应用

数字聚合酶链反应(polymerase chain reaction,PCR)采用与定量PCR相同的荧光化学原理和不同的数学原理来实现对靶标核酸序列的绝对定量,其摒弃了对外部参照的依赖,同时具有更高的数据精密度,提高了重复性和再现性。数字PCR的应用涵盖生命科学众多领域,特别是在医学检验领域,其对疾病相关核酸分子标记的准确分析,为疾病的早期诊断、进展监测、疗效评估提供了动态量化指标。数字PCR的出现将推动基于核酸扩增技术的分子生物学检测迈入精准定量阶段。本文就数字PCR尤其是微滴式数字PCR在感染性疾病中的应用进展及前沿进行综述。     

Proteomics in clinical interventions: achievements and limitations in biomarker development

Development of toxicological and clinical biomarkers for disease diagnosis, quantification of toxicant/drug responses and rapid patient care are major concerns in modern biology. Even after human genome sequencing, identification of specific molecular signatures for unambiguous correlation with toxicity and clinical interventions is a challenging task. Differential protein expression patterns and protein-protein interaction studies have started unraveling rigorous molecular explanation of multi-factorial and toxicant borne diseases. Proteome profiling is extensively used to investigate etiology of diseases, develop predictive biomarkers for toxicity and therapeutic interventions and potential strategies for treatment of complex and toxicant mediated diseases. In this review, achievements and limitations of proteomics in developing predictive biomarkers for toxicological and clinical interventions have been discussed.     

Design and development of opto-electrochemical biosensing devices for diagnosing chronic kidney disease

Chronic kidney disease (CKD) is emerging as one of the major causes of the increase in mortality rate and is expected to become 5th major cause by 2050. Many studies have shown that it is majorly related to various risk factors, and thus becoming one of the major health issues around the globe. Early detection of renal disease lowers the overall burden of disease by preventing individuals from developing kidney impairment. Therefore, diagnosis and prevention of CKD are becoming the major challenges, and in this situation, biosensors have emerged as one of the best possible solutions. Biosensors are becoming one of the preferred choices for various diseases diagnosis as they provide simpler, cost-effective and precise methods for onsite detection. In this review, we have tried to discuss the globally developed biosensors for the detection of CKD, focusing on their design, pattern, and applicability in real samples. Two major classifications of biosensors based on transduction systems, that is, optical and electrochemical, for kidney disease have been discussed in detail. Also, the major focus is given to clinical biomarkers such as albumin, creatinine, and others related to kidney dysfunction. Furthermore, the globally developed sensors for the detection of CKD are discussed in tabulated form comparing their analytical performance, response time, specificity as well as performance in biological fluids.     

High resolution proteome/peptidome analysis of body fluids by capillary electrophoresis coupled with MS

All organisms contain thousands of proteins and peptides in their body fluids. A deeper insight into the functional relevance of these polypeptides under different physiological and pathophysiological conditions and the discovery of specific peptide biomarkers would greatly enhance both diagnosis and therapy of specific diseases. Proteomic methods can provide means to accomplish this grand medical vision. In this review, we will focus on the potential use of proteome analysis for clinical applications, such as disease diagnosis and assessment of response to therapy. We focus on CE coupled with MS (CE-MS) and review in detail different aspects of CE-MS coupling and the results obtained using CE-MS analysis of clinically relevant samples. We also discuss clinical applications of the technology for the diagnosis of renal diseases, urogenital cancer, and arteriosclerosis as well as monitoring the responses to therapeutic interventions.     

Microfluidic-integrated biosensors: Prospects for point-of-care diagnostics

There is a growing demand to integrate biosensors with microfluidics to provide miniaturized platforms with many favorable properties, such as reduced sample volume, decreased processing time, low cost analysis and low reagent consumption. These microfluidics-integrated biosensors would also have numerous advantages such as laminar flow, minimal handling of hazardous materials, multiple sample detection in parallel, portability and versatility in design. Microfluidics involves the science and technology of manipulation of fluids at the micro- to nano-liter level. It is predicted that combining biosensors with microfluidic chips will yield enhanced analytical capability, and widen the possibilities for applications in clinical diagnostics. The recent developments in microfluidics have helped researchers working in industries and educational institutes to adopt some of these platforms for point-of-care (POC) diagnostics. This review focuses on the latest advancements in the fields of microfluidic biosensing technologies, and on the challenges and possible solutions for translation of this technology for POC diagnostic applications. We also discuss the fabrication techniques required for developing microfluidic-integrated biosensors, recently reported biomarkers, and the prospects of POC diagnostics in the medical industry.     

MicroRNAs as potential investigative and predictive biomarkers in colorectal cancer

Colorectal cancer (CRC) is a noticeable reason of cancer-associated deaths with a high incidence and mortality rate. Countless effort have been put into the improving clinical management of CRC patients including more effective tools and a wide variety of biomarkers for diagnostic, prognostic or predictive purposes. In recent years, dysregulated miRNAs have been emerged as highly sensitive and specific markers to manage CRC in an effective way. They can play key roles in carcinogenesis as potential oncogenes, tumor suppressors or regulators of cancer network. Therefore, miRNAs may serve as molecular tools that can be quantified and used in diagnostic and prognostic approaches. Growing evidence also suggests that forced expression of tumor suppressor miRNAs or inhibiting the oncogene ones, can be used as a novel treatment strategy. In this review, we focus on the clinical applications of miRNAs as promising biomarkers of early cancer detection, prognosis and treatment.     

场效应晶体管生物传感器在生物医学检测中的应用研究进展*

场效应晶体管生物传感器因其灵敏度高、分析速度快、无标记、体积小、操作简单等特点而受到了很多关注,广泛应用于DNA、蛋白质、细胞、离子等生物识别物的检测。近年来,更有纳米材料和微电子技术在传感器设计中提高传感器的传感性能,场效应晶体管生物传感器朝着高灵敏、微型化、快速化以及多功能化的方向以令人惊叹的速度发展。研究场效应晶体管生物传感器工作原理,阐述近年来场效应晶体管生物传感器在生物医学检测领域中最新的研究进展与应用,探讨场效应晶体管生物传感器克服各种缺陷的应对策略,为该传感器在未来生物医学检测中的开发提供参考。     

The present and the future of protein biosensor engineering

Protein biosensors play increasingly important roles in cell and neurobiology and have the potential to revolutionise the way clinical and industrial analytics are performed. The gradual transition from multicomponent biosensors to fully integrated single chain allosteric biosensors has brought the field closer to commercial applications. We evaluate various approaches for converting constitutively active protein reporter domains into analyte operated switches. We discuss the paucity of the natural receptors that undergo conformational changes sufficiently large to control the activity of allosteric reporter domains. This problem can be overcome by constructing artificial versions of such receptors. The design path to such receptors involves the construction of Chemically Induced Dimerisation systems (CIDs) that can be configured to operate single and two-component biosensors.     

Biosensors for biomarkers in medical diagnostics

At present, most biomarker testing is taking place at centralised dedicated laboratories using large, automated analysers, increasing waiting time and costs. Smaller, faster and cheaper devices are highly desired for replacing these time-consuming laboratory analyses and for making analytical results available at the patient's bedside (point-of-care diagnostics). Innovative biosensor-based strategies could allow biomarkers to be tested reliably in a decentralised setting, although several challenges and limitations remain, which need to be improved, in the design and application of biosensors for the appropriate interpretation of the identified and quantified biomarkers. The development of biosensors is probably one of the most promising ways to solve some of the problems concerning the increasing need to develop highly sensitive, fast and economic methods of analysis in medical diagnostics. In this review, some consideration will be given to biosensors and their application in medical diagnostics, taking into account several crucial features.     

Artificial intelligence and machine learning for medical imaging: A technology review

Artificial intelligence (AI) has recently become a very popular buzzword, as a consequence of disruptive technical advances and impressive experimental results, notably in the field of image analysis and processing. In medicine, specialties where images are central, like radiology, pathology or oncology, have seized the opportunity and considerable efforts in research and development have been deployed to transfer the potential of AI to clinical applications. With AI becoming a more mainstream tool for typical medical imaging analysis tasks, such as diagnosis, segmentation, or classification, the key for a safe and efficient use of clinical AI applications relies, in part, on informed practitioners. The aim of this review is to present the basic technological pillars of AI, together with the state-of-the-art machine learning methods and their application to medical imaging. In addition, we discuss the new trends and future research directions. This will help the reader to understand how AI methods are now becoming an ubiquitous tool in any medical image analysis workflow and pave the way for the clinical implementation of AI-based solutions.     

Human saliva proteome analysis and disease biomarker discovery

Human saliva is an attractive body fluid for disease diagnosis and prognosis because saliva testing is simple, safe, low-cost and noninvasive. Comprehensive analysis and identification of the proteomic content in human whole and ductal saliva will not only contribute to the understanding of oral health and disease pathogenesis, but also form a foundation for the discovery of saliva protein biomarkers for human disease detection. In this article, we have summarized the proteomic technologies for comprehensive identification of proteins in human whole and ductal saliva. We have also discussed potential quantitative proteomic approaches to the discovery of saliva protein biomarkers for human oral and systemic diseases. With the fast development of mass spectrometry and proteomic technologies, we are enthusiastic that saliva protein biomarkers will be developed for clinical diagnosis and prognosis of human diseases in the future.     

Human saliva proteome analysis and disease biomarker discovery

Human saliva is an attractive body fluid for disease diagnosis and prognosis because saliva testing is simple, safe, low-cost and noninvasive. Comprehensive analysis and identification of the proteomic content in human whole and ductal saliva will not only contribute to the understanding of oral health and disease pathogenesis, but also form a foundation for the discovery of saliva protein biomarkers for human disease detection. In this article, we have summarized the proteomic technologies for comprehensive identification of proteins in human whole and ductal saliva. We have also discussed potential quantitative proteomic approaches to the discovery of saliva protein biomarkers for human oral and systemic diseases. With the fast development of mass spectrometry and proteomic technologies, we are enthusiastic that saliva protein biomarkers will be developed for clinical diagnosis and prognosis of human diseases in the future.