Oncometabolomics in cancer research

Cancer is not only a complex genetic disease, but also a disease of dysregulated bioenergetic metabolism. With improved technological advancements, the focus has shifted from changes in an individual biochemical pathway or metabolite toward changes in the context of the global network of metabolic pathways in a cell, tissue or organism. This global approach allows identifying changes in the pattern of metabolite expression in addition to changes in individual metabolite or pathway. Such a metabolomics approach promises a better understanding of tumor biology and identification of potential biomarkers with applications as diagnostic, prognostic and therapeutic targets. In this review, we discuss various techniques used in metabolomics and analysis of the data generated and its specific uses in cancer research including novel biomarker identification, development of more sensitive and specific diagnostic methods, monitoring of currently used cancer therapeutics to evaluate the prognostic outcome with a given therapy and evaluating novel therapeutic strategies.     

Implications of new proteomics strategies for biology and medicine

Advances in proteomics have fundamentally changed the paradigm of discovery for drug targets and novel biomarkers. Proteomics methodologies currently used will be reviewed in this paper, including structural proteomics, quantitative proteomics, and functional proteomics. A strategy to identify differentially expressed cell surface proteins as monoclonal therapeutic targets in oncology will be discussed.     

Oncoproteomics: current trends and future perspectives

Oncoproteomics is the application of proteomics technologies in oncology. Functional proteomics is a promising technique for the rational identification of biomarkers and novel therapeutic targets for cancers. Recent progress in proteomics has opened new avenues for tumor-associated biomarker discovery. With the advent of new and improved proteomics technologies, such as the development of quantitative proteomic methods, high-resolution, -speed and -sensitivity mass spectrometry and protein arrays, as well as advanced bioinformatics for data handling and interpretation, it is now possible to discover biomarkers that can reliably and accurately predict outcomes during cancer management and treatment. However, there are several difficulties in the study of proteins/peptides that are not inherent in the study of nucleic acids. New challenges arise in large-scale proteomic profiling when dealing with complex biological mixtures. Nevertheless, oncoproteomics offers great promise for unveiling the complex molecular events of tumorigenesis, as well as those that control clinically important tumor behaviors, such as metastasis, invasion and resistance to therapy. In this review, the development and advancement of oncoproteomics technologies for cancer research in recent years are expounded.     

Oncoproteomics: current trends and future perspectives

Oncoproteomics is the application of proteomics technologies in oncology. Functional proteomics is a promising technique for the rational identification of biomarkers and novel therapeutic targets for cancers. Recent progress in proteomics has opened new avenues for tumor-associated biomarker discovery. With the advent of new and improved proteomics technologies, such as the development of quantitative proteomic methods, high-resolution, -speed and -sensitivity mass spectrometry and protein arrays, as well as advanced bioinformatics for data handling and interpretation, it is now possible to discover biomarkers that can reliably and accurately predict outcomes during cancer management and treatment. However, there are several difficulties in the study of proteins/peptides that are not inherent in the study of nucleic acids. New challenges arise in large-scale proteomic profiling when dealing with complex biological mixtures. Nevertheless, oncoproteomics offers great promise for unveiling the complex molecular events of tumorigenesis, as well as those that control clinically important tumor behaviors, such as metastasis, invasion and resistance to therapy. In this review, the development and advancement of oncoproteomics technologies for cancer research in recent years are expounded.     

Pharmaco-metabolomics: an emerging "omics" tool for the personalization of anticancer treatments and identification of new valuable therapeutic targets

In the post-genomics era, metabolomics represents a new "omics" approach that in the last decade has received increased attention in the field of oncology. Metabolomics is based on the holistic study of the metabolic profile that characterizes a specific phenotype in a biological system. The metabolic profile provides a readout of the metabolic state of an individual that cannot be obtained directly from DNA genotyping, gene expression, or proteomic profiling analyses. The translational value of metabonomics in the oncology field has been demonstrated by the identification of diagnostic and prognostic biomarkers. The so-called pharmaco-metabolomic approach that is currently emerging aims to identify the individual metabolomic characteristics able to predict drug effectiveness and/or toxicity. This review presents the potential role of pharmaco-metabolomics in the future of anticancer pharmacology to achieve customized anticancer treatments and new, targeted therapeutic approaches.     

Proteomics of breast cancer: From differential to functional analysis

From differential analysis to identify biomarkers, to functional analysis for finding new therapeutic targets, proteomics bring new comprehensive information for a better understanding of the molecular basis of oncology and new perspectives for the clinic. However the major limitation of proteomic investigations, more generally of post-genomic approaches, remains the molecular and cellular complexity of the mammary gland that is still a major challenge.     

Renal and urinary proteomics: current applications and challenges

During the past few years, proteomics has been extensively applied to various fields of medicine including nephrology. Current applications of renal and urinary proteomics are to better understand renal physiology, to explore the complexity of disease mechanisms, and to identify novel biomarkers and new therapeutic targets. This review provides some examples and perspectives of how proteomics can be applied to nephrology and how experimental data can be linked to physiology, functional significance and clinical applications. In some instances, proteomic analysis can be utilized to generate a new hypothesis from a set of candidates that are obtained from expression studies. The new hypothesis can then be addressed rapidly by conventional molecular biology methods, as demonstrated by identification of an altered renal elastin-elastase system in diabetic nephropathy and alterations in the renal kallikrein-kallistatin pathway in hypoxia-induced hypertension. The strengths and limitations of proteomics in renal research are summarized. Optimization of analytical protocols is required to overcome current limitations. Applications of proteomics to nephrology will then be more fruitful and successful.     

Urinary proteomics and molecular determinants of chronic kidney disease: possible link to proteases

Chronic kidney disease (CKD) is the gradual decrease in renal function. Currently available biomarkers are effective only in detecting late stage CKD. Biomarkers of early stage CKD and prognostic biomarkers are required. We review the major findings in urinary proteomics in CKD during the last five years. Significant progress has been made and today urinary proteomics is applied in large randomized trials, and in patient management. Many of the biomarkers indicate altered protease activity. We therefore also review the literature on proteases associated with renal function loss. We anticipate in silico prediction tools of protease activity and additional system biology studies may contribute to biomarker discovery and elucidate the role of proteases in CKD development and progression. These approaches will enable the deciphering of the molecular pathophysiology of CKD, and hence definition of the most appropriate therapeutic targets in the future. Together with stable biomarker panels available today, this will significantly improve patient management.     

Proteomic analysis of renal diseases: unraveling the pathophysiology and biomarker discovery

Current biomedical applications of proteomics have been conducted with four main objectives: to better understand the normal biology and physiology of cells, microorganisms, tissues and organs; to explore the pathogenic mechanisms and better understand the pathophysiology of medical diseases; to identify novel biomarkers for early disease detection, prediction and prognosis; and to define new therapeutic targets, drugs and vaccines. This review focuses predominantly on proteomic applications to unravel the pathophysiology and to define novel biomarkers for various renal diseases (i.e., glomerular diseases, tubulointerstitial diseases, renal vascular disorders and renal cancers). In addition, proteomic evaluations of renal transplantation and renal replacement therapy (for acute renal failure and end-stage renal disease) are summarized. Personal opinion, future perspectives and information resources for the field of renal and urinary proteomics are provided.     

Mass spectrometric proteomics profiles of in vivo tumor secretomes: capillary ultrafiltration sampling of regressive tumor masses

Identification of in vivo secreted peptides/proteins (secretomes) in tumor masses has the potential to provide important biomarkers and therapeutic targets for cancer therapy. However, limitations of existing technologies have made obtaining these secretomes for analysis extremely difficult. Here we employed an in vivo sampling technique using capillary ultrafiltration (CUF) probes to collect secretomes directly from tumor masses. Mass spectrometric proteomics approaches were then used to identify the tumor secretomes. A UV-induced skin fibrosarcoma cell line (UV-2240) was subcutaneously injected into C3H/NeH mice, resulting in tumor masses that initially progressed, then regressed and eventually eradicated. We then implanted CUF probes into tumor masses at the progressive and regressive stage. Five secreted proteins (cyclophilin-A, S100A4, profilin-1, thymosin beta 4 and 10), previously associated with tumor progression, were identified from tumor masses at the progressive stage. Five secreted proteins including three protease inhibitors (fetuin-A, alpha-1 antitrypsin 1-6, and contrapsin) were identified from tumor masses at the regressive stage. The technique involving CUF probes linked to mass spectrometric proteomics reinforces systems biology studies of cell-cell interactions and is potentially applicable to the discovery of in vivo biomarkers in human disease.     

Proteomic analysis of renal diseases: unraveling the pathophysiology and biomarker discovery

Current biomedical applications of proteomics have been conducted with four main objectives: to better understand the normal biology and physiology of cells, microorganisms, tissues and organs; to explore the pathogenic mechanisms and better understand the pathophysiology of medical diseases; to identify novel biomarkers for early disease detection, prediction and prognosis; and to define new therapeutic targets, drugs and vaccines. This review focuses predominantly on proteomic applications to unravel the pathophysiology and to define novel biomarkers for various renal diseases (i.e., glomerular diseases, tubulointerstitial diseases, renal vascular disorders and renal cancers). In addition, proteomic evaluations of renal transplantation and renal replacement therapy (for acute renal failure and end-stage renal disease) are summarized. Personal opinion, future perspectives and information resources for the field of renal and urinary proteomics are provided.     

Proteomics of hepatocellular carcinoma in Chinese patients

Hepatocellular carcinoma (HCC) is a malignant tumor of liver that causes approximately half a million deaths each year, of which over half of the cases are diagnosed in China. Because of its asymptomatic nature, HCC is usually diagnosed at late and advanced stages, for which there are no effective therapies. Thus, biomarkers for early detection and molecular targets for treating HCC are urgently needed. With the advent of high-throughput omics technologies, we have begun to mine the genomics and proteomics information of HCC, and most importantly, these data can be integrated with clinical annotations of the patients. Such new horizons of integrated profiling informatics have allowed us to search for and better identify clinically useful biomarkers and therapeutic targets for cancers including HCC. Capitalizing the large clinical samples cohort (over 100 pairs of tumor and matched adjacent nontumor tissues of HCC), we herein discuss the use of proteomics approach to identify biomarkers that are potentially useful for (1) discrimination of tumorous from nonmalignant tissues, (2) detection of small-sized and early stage of HCC, and (3) prediction of early disease relapse after hepatectomy.     

Application of proteomics in non-small-cell lung cancer

Non-small-cell lung cancer (NSCLC) is a heterogeneous disease with diverse pathological features. Clinical proteomics allows the discovery of molecular markers and new therapeutic targets for this most prevalent type of lung cancer. Some of them may be used to detect early lung cancer, while others may serve as predictive markers of resistance to different therapies. Therapeutic targets and prognostic markers in NSCLC have also been discovered. These proteomics biomarkers may help to pair the individual NSCLC patient with the best treatment option. Despite the fact that implementation of these biomarkers in the clinic appears to be scarce, the recently launched Precision Medicine Initiative may encourage their translation into clinical practice.     

Biomarker Discovery in Human Prostate Cancer: an Update in Metabolomics Studies

Prostate cancer (PCa) is the most frequently diagnosed cancer and the second leading cause of cancer death among men in Western countries. Current screening techniques are based on the measurement of serum prostate specific antigen (PSA) levels and digital rectal examination. A decisive diagnosis of PCa is based on prostate biopsies; however, this approach can lead to false-positive and false-negative results. Therefore, it is important to discover new biomarkers for the diagnosis of PCa, preferably noninvasive ones. Metabolomics is an approach that allows the analysis of the entire metabolic profile of a biological system. As neoplastic cells have a unique metabolic phenotype related to cancer development and progression, the identification of dysfunctional metabolic pathways using metabolomics can be used to discover cancer biomarkers and therapeutic targets. In this study, we review several metabolomics studies performed in prostatic fluid, blood plasma/serum, urine, tissues and immortalized cultured cell lines with the objective of discovering alterations in the metabolic phenotype of PCa and thus discovering new biomarkers for the diagnosis of PCa. Encouraging results using metabolomics have been reported for PCa, with sarcosine being one of the most promising biomarkers identified to date. However, the use of sarcosine as a PCa biomarker in the clinic remains a controversial issue within the scientific community. Beyond sarcosine, other metabolites are considered to be biomarkers for PCa, but they still need clinical validation. Despite the lack of metabolomics biomarkers reaching clinical practice, metabolomics proved to be a powerful tool in the discovery of new biomarkers for PCa detection.     

非酒精性脂肪性肝病蛋白质组学研究进展

非酒精性脂肪性肝病(nonalcoholic fatty liver disease,NAFLD)是一种常见慢性肝脏疾病,其发病率呈逐年上升趋势,但发病机制尚未明确,诊疗手段仍不完善.蛋白质组学(proteomics)的出现使NAFLD研究有了进一步的发展,相关研究已达21个.目前,蛋白质组学技术可以研究疾病相关的分子改变,从而寻找新的生物标志物和治疗靶标.在此,对蛋白质组学在NAFLD诊断及分期、发病机制和其他相关领域研究进展作一个较为全面的综述.首先,对研究中遇到的研究对象、样本种类、实验方法和标志物特征选择进行经验性总结.其次,除了介绍如何运用蛋白质组学研究病因、危险因素和重要分子在NAFLD发病机制中的作用,还介绍NAFLD发病机制的亚细胞蛋白质组学、修饰蛋白质组学以及蛋白质组学与转录组学相结合的研究实例.此外,对差异蛋白质的分析策略和价值作了重点阐述,收集到一些有望成为NAFLD治疗靶标的候选分子.最后,结合新技术展望研究新空间,以期能够有助于推动蛋白质组学在寻找新的疾病标志物、探索疾病分子机制和治疗靶标中开辟新的途径.     

Invitrogen & HUPO enter partnership

Neuroblastoma (NB) is one of the most common solid tumors of childhood and displays a remarkable diversity in both biologic characteristics and clinical outcomes. Availability of high-throughput ‘omics technologies and their subsequent application towards oncology has provided insight into the complex pathways of tumor formation and progression. Investigation of NB ‘omics profiles may better define tumor behavior and provide targeted therapy with the goal of improving outcomes in patients with high-risk disease. Utilization of these technologies in NB has already led to advances in classification and risk stratification. The gradual emergence of NB-directed proteomics adds a layer of intricacy to the analysis of biologic organization but may ultimately provide a better comprehension of this complex disease. In this review, we cite specific examples of how NB-directed proteomics has provided information regarding novel biomarkers and possible therapeutic targets. We finish by examining the impact of high-throughput ‘omics in the field of NB and speculate on how these emerging technologies may further be incorporated into the discipline.     

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.