Challenges of using mass spectrometry as a bladder cancer biomarker discovery platform

Hydroxymethylation and tumors: can 5-hydroxymethylation be used as a marker for tumor diagnosis and treatment?

5-Methylcytosine (5mC) is considered as a common epigenetic modification that plays an important role in the regulation of gene expression. At the same time, 5-hydroxymethylcytosine (5hmC) has been found as an emerging modification of cytosine bases of recent years. Unlike 5mC, global 5hmC levels vary from tissues that have differential distribution both in mammalian tissues and in the genome. DNA hydroxymethylation is the process that 5mC oxidates into 5hmC with the catalysis of TET (ten-eleven translocation) enzymes. It is an essential option of DNA demethylation, which modulates gene expression by adjusting the DNA methylation level. Various factors can regulate the demethylation of DNA, such as environmental toxins and mental stress. In this review, we summarize the progress in the formation of 5hmC, and obtaining 5hmC in a cell-free DNA sample presents multiple advantages and challenges for the subject. Furthermore, the clinical potential for 5hmC modification in dealing with cancer early diagnosis, prognostic evaluation, and prediction of therapeutic effect is also mentioned.

Approaches to the discovery of non-invasive urinary biomarkers of prostate cancer

Prostate cancer (PCa) continues to be one of the most common cancers in men worldwide. Prostate specific antigen (PSA) measured in blood has been used for decades as an aid for physicians to detect the presence of prostate cancer. However, the PSA test has limited sensitivity and specificity, leading to unnecessary biopsies, overdiagnosis and overtreatment of patients. For these reasons, there is an urgent need for more accurate PCa biomarkers that can detect PCa with high sensitivity and specificity. Urine is a unique source of potential protein biomarkers that can be measured in a non-invasive way. This review comprehensively summarizes state of the art approaches used in the discovery and validation of urinary biomarkers for PCa. Numerous strategies are currently being used in the discovery of urinary biomarkers for prostate cancer including gel-based separation techniques, mass spectrometry, activity-based proteomic assays and software approaches. Antibody-based approaches remain preferred method for validation of candidate biomarkers with rapidly advancing multiplex immunoassays and MS-based targeted approaches. In the last decade, there has been a dramatic acceleration in the development of new techniques and approaches in the discovery of protein biomarkers for prostate cancer including computational, statistical and data mining methods. Many urinary-based protein biomarkers have been identified and have shown significant promise in initial studies. Examples of these potential biomarkers and the methods utilized in their discovery are also discussed in this review.

The impact of advanced proteomics in the search for markers and therapeutic targets of bladder cancer

Bladder cancer is the most common cancer of the urinary tract and can be avoided through proper surveillance and monitoring. Several genetic factors are known to contribute to the progression of bladder cancer, many of which produce molecules that serve as cancer biomarkers. Blood, urine, and tissue are commonly analyzed for the presence of biomarkers, which can be derived from either the nucleus or the mitochondria. Recent advances in proteomics have facilitated the high-throughput profiling of data generated from bladder cancer-related proteins or peptides in parallel with high sensitivity and specificity, providing a wealth of information for biomarker discovery and validation. However, the transmission of screening results from one laboratory to another remains the main disadvantage of these methods, a fact that emphasizes the need for consistent and standardized procedures as suggested by the Human Proteome Organization. This review summarizes the latest discoveries and progress of biomarker identification for the early diagnosis, projected prognosis, and therapeutic response of bladder cancer, informs the readers of the current status of proteomic-based biomarker findings, and suggests avenues for future work.

Integrated technologies in the post-genomic era for discovery of bladder cancer urinary markers

The incidence of bladder cancer (BC) continues to rise with high recurrence and mortality rate, especially in the past three decades. The development of accurate and successful BC treatment relies mainly on early diagnosis. BC is a heterogeneous disease reflected by the presence of many potential biomarkers associated with different disease phenotypes. Nowadays, cystoscopy and urinary cytology are considered the gold standard diagnostic tools for BC. There are many limitations to cystoscopy including being invasive, labor-intensive and carcinoma in situ of the bladder may easily be missed. Urinary cytology is still a noninvasive technique with high accuracy in high-grade BC with a median sensitivity of 35%. Furthermore, the need for a sensitive, specific, non invasive, easily accessible BC biomarker is a major clinical need. The field of urinary BC biomarkers discovery is still a rapidly evolving discipline in which more recent technologies are evaluated and often optimized if they are not clinically significant to the urologists. Most of the current strategies for BC urinary biomarker detection depend on integration of information gleaned from the fields of genomics, transcriptomics, proteomics, epigenetics, metabolomics and bionanotechnology. Effort is currently being made to identify the most potentially beneficial urinary biomarkers. The purpose of this review is to summarize and explore the efficacy of gathering the information revealed from the cooperation of different omic strategies that paves the way towards various urinary markers discovery for screening, diagnosis and prognosis of human BC.

Proteomics in hypertension and other cardiovascular diseases

Hypertension is a major cardiovascular risk factor with a multifactorial pathogenesis, including genetic and environmental factors. In addition to hypothesis-driven strategies, unbiased approaches such as genomics, proteomics, and metabolomics are useful tools to help unravel the pathophysiology of hypertension and associated organ damage. During development of cardiovascular disease the key organs and tissues undergo extensive functional and structural changes that are characterized by alterations in the amount and type of proteins that are expressed. Proteomic approaches study the expression of large numbers of proteins in organs, tissues, cells, and body fluids. A number of different proteomic platforms are available, many of which combine two methods to separate proteins and peptides after an initial digestion step. Identification of these peptides and changes in their expression in parallel with disease processes or medical treatment will help to identify as yet unknown pathophysiological pathways. There is also potential to use proteomic signatures as biomarkers of cardiovascular disease that will contribute to population screening, diagnosis of diseases and their severity, and monitoring of therapeutic interventions.

Proteomic tissue profiling for the improvement of grading of noninvasive papillary urothelial neoplasia

OBJECTIVES

In 2004, a novel grading system for papillary non-invasive bladder cancer was introduced; low grade (LG) and high grade (HG) in lieu of the former G1, G2, G3. This change allowed for increased reproducibility as well as diminished interobserver variability in histopathological grading among individual pathologists. Matrix Assisted Laser Desorption/Ionization Time of Flight Imaging Mass Spectrometry (MALDI TOF IMS) was evaluated as an automatic and objective tool to assist grading of urothelial neoplasms and to facilitate accuracy.

DESIGN AND METHODS

To separate G1 (LG, n=27) and G3 (HG, n=21) papillary tumors MALDI TOF IMS was performed using an appropriate algorithm. Thereafter, the automatic assignment of a separate G2 (n=31) group was completed.

RESULTS

G1 (LG) and G3 (HG) tumors were separated with an overall cross validation of 97.18%. G2 tumors indicated a true positive rate of 78.3% for LG and 87.5% for HG, respectively.

CONCLUSIONS

MALDI TOF IMS is a powerful support tool to ascertain pathological diagnosis/grading.

Urine proteomics in kidney and urogenital diseases: Moving towards clinical applications

To date, multiple biomarker discovery studies in urine have been conducted. Nevertheless, the rate of progression of these biomarkers to qualification and even more clinical application is extremely low. The scope of this article is to provide an overview of main clinically relevant proteomic findings from urine focusing on kidney diseases, bladder and prostate cancers. In addition, approaches for promoting the use of urine in clinical proteomics including potential means to facilitate the validation of existing promising findings (biomarker candidates identified from previous studies) and to increase the chances for success for the identification of new biomarkers are discussed.

Methods for the discovery of low-abundance biomarkers for urinary bladder cancer in biological fluids

For the study of bladder cancer and the identification of respective tumor markers, blood and, in particular, urine constitute suitable sources of biological material, while both harboring their specific challenges for analytics concerning low-abundance biomarkers. Dissolved proteins and nucleic acids as well as cells and cell-bound molecules can be the analytes. In urine, exfoliated bladder tumor cells have to be identified and in blood, circulating tumor cells have to be detected among huge amounts of other cells. For the detection of both low-abundance cells and molecules, their specific enrichment prior to analysis is advantageous or even necessary. Adapted methods for the analysis of proteomes and subproteomes by 2D-gel electrophoresis, multidimensional chromatography and antibody arrays are discussed. Analysis of nucleic acid-based markers exploits the high amplification power of PCR and modified PCR combined with previous (subtransciptomes) or subsequent (microarray) enrichment to sensitively and specifically detect markers. DNA mutations, DNA-methylation status and apoptotic DNA fragments, as well as levels of ribonucleic acids including microRNAs, can be analyzed by means of these methods. Finally, the challenge of identifying circulating tumor cells and assigning them to their original tissue is critically discussed.

Discovery of novel bladder cancer biomarkers by comparative urine proteomics using iTRAQ technology

A urine sample preparation workflow for the iTRAQ (isobaric tag for relative and absolute quantitation) technique was established. The reproducibility of this platform was evaluated and applied to discover proteins with differential levels between pooled urine samples from nontumor controls and three bladder cancer patient subgroups with different grades/stages (a total of 14 controls and 23 cancer cases in two multiplex iTRAQ runs). Combining the results of two independent clinical sample sets, a total of 638 urine proteins were identified. Among them, 55 proteins consistently showed >2-fold differences in both sample sets. Western blot analyses of individual urine samples confirmed that the levels of apolipoprotein A-I (APOA1), apolipoprotein A-II, heparin cofactor 2 precursor and peroxiredoxin-2 were significantly elevated in bladder cancer urine specimens (n = 25-74). Finally, we quantified APOA1 in a number of urine samples using a commercial ELISA and confirmed again its potential value for diagnosis (n = 126, 94.6% sensitivity and 92.0% specificity at a cutoff value of 11.16 ng/mL) and early detection (n = 71, 83.8% sensitivity and 94.0% specificity). Collectively, our results provide the first iTRAQ-based quantitative profile of bladder cancer urine proteins and represent a valuable resource for the discovery of bladder cancer markers.

Capillary electrophoresis mass spectrometry-based saliva metabolomics identified oral, breast and pancreatic cancer-specific profiles

Saliva is a readily accessible and informative biofluid, making it ideal for the early detection of a wide range of diseases including cardiovascular, renal, and autoimmune diseases, viral and bacterial infections and, importantly, cancers. Saliva-based diagnostics, particularly those based on metabolomics technology, are emerging and offer a promising clinical strategy, characterizing the association between salivary analytes and a particular disease. Here, we conducted a comprehensive metabolite analysis of saliva samples obtained from 215 individuals (69 oral, 18 pancreatic and 30 breast cancer patients, 11 periodontal disease patients and 87 healthy controls) using capillary electrophoresis time-of-flight mass spectrometry (CE-TOF-MS). We identified 57 principal metabolites that can be used to accurately predict the probability of being affected by each individual disease. Although small but significant correlations were found between the known patient characteristics and the quantified metabolites, the profiles manifested relatively higher concentrations of most of the metabolites detected in all three cancers in comparison with those in people with periodontal disease and control subjects. This suggests that cancer-specific signatures are embedded in saliva metabolites. Multiple logistic regression models yielded high area under the receiver-operating characteristic curves (AUCs) to discriminate healthy controls from each disease. The AUCs were 0.865 for oral cancer, 0.973 for breast cancer, 0.993 for pancreatic cancer, and 0.969 for periodontal diseases. The accuracy of the models was also high, with cross-validation AUCs of 0.810, 0.881, 0.994, and 0.954, respectively. Quantitative information for these 57 metabolites and their combinations enable us to predict disease susceptibility. These metabolites are promising biomarkers for medical screening. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11306-009-0178-y) contains supplementary material, which is available to authorized users.

Potential new urinary markers in the early detection of bladder cancer

PURPOSE OF REVIEW

Bladder cancer remains a highly prevalent and lethal malignancy. Early diagnosis and prompt treatment have been shown to improve survival at both initial diagnosis and recurrence. A vast number of tumor markers have been identified and rigorously evaluated in attempts to improve noninvasive diagnostic accuracy of bladder cancer. Hematuria was the first tumor marker in a field that has grown to include soluble markers, cell-surface antigens, cell-cycle-related proteins, and genetic alterations. We aim to provide a critical appraisal of newer markers and the current state of research.

RECENT FINDINGS

The number of tumor markers identified has been exponentially increasing. For a variety of reasons, many are unsuitable for clinical practice. More promising recent markers include those discovered in the fields of genomics, proteomics, and epigenetics. Much of the recent work is focused on molecular genetic pathways in bladder cancer.

SUMMARY

The field of bladder cancer tumor markers remains a rapidly evolving area in which newer markers are constantly identified, evaluated, and often discarded if they do not add significantly to the urologists' armamentarium. Newer markers rely on genetic rearrangements, molecular changes, and cell-cycle-related proteins. Work is currently being done to identify the most promising markers.

Sources of Urinary Proteins and their Analysis by Urinary Proteomics for the Detection of Biomarkers of Disease

Renal disorders account for a substantial fraction of the budget for health care in many countries. Proteinuria is a frequent manifestation in afflicted patients, but the origin of the proteins varies based on the nature of the disorder. The emerging field of urinary proteomics has the potential to replace kidney biopsy as the diagnostic procedure of choice for patients with some glomerular forms of renal disease. To fully realize this potential, it is vital to understand the basis for the urinary excretion of protein in physiological and pathological conditions. In this review, we discuss the structure of the nephron, the functional unit of the kidney, and the process by which proteins/peptides enter the urine. We discuss several aspects of proteinuria that impact the proteomic analysis of urine of patients with renal diseases.

An introduction to artificial neural networks in bioinformatics--application to complex microarray and mass spectrometry datasets in cancer studies

Applications of genomic and proteomic technologies have seen a major increase, resulting in an explosion in the amount of highly dimensional and complex data being generated. Subsequently this has increased the effort by the bioinformatics community to develop novel computational approaches that allow for meaningful information to be extracted. This information must be of biological relevance and thus correlate to disease phenotypes of interest. Artificial neural networks are a form of machine learning from the field of artificial intelligence with proven pattern recognition capabilities and have been utilized in many areas of bioinformatics. This is due to their ability to cope with highly dimensional complex datasets such as those developed by protein mass spectrometry and DNA microarray experiments. As such, neural networks have been applied to problems such as disease classification and identification of biomarkers. This review introduces and describes the concepts related to neural networks, the advantages and caveats to their use, examples of their applications in mass spectrometry and microarray research (with a particular focus on cancer studies), and illustrations from recent literature showing where neural networks have performed well in comparison to other machine learning methods. This should form the necessary background knowledge and information enabling researchers with an interest in these methodologies, but not necessarily from a machine learning background, to apply the concepts to their own datasets, thus maximizing the information gain from these complex biological systems.

Urine in clinical proteomics

Urine has become one of the most attractive biofluids in clinical proteomics as it can be obtained non-invasively in large quantities and is stable compared with other biofluids. The urinary proteome has been studied by almost any proteomics technology, but mass spectrometry-based urinary protein and peptide profiling has emerged as most suitable for clinical application. After a period of descriptive urinary proteomics the field is moving out of the discovery phase into an era of validation of urinary biomarkers in larger prospective studies. Although mainly due to the site of production of urine, the majority of these studies apply to the kidney and the urinary tract, but recent data show that analysis of the urinary proteome can also be highly informative on non-urogenital diseases and used in their classification. Despite this progress in urinary biomarker discovery, the contribution of urinary proteomics to the understanding of the pathophysiology of disease upon analysis of the urinary proteome is still modest mainly because of problems associated to sequence identification of the biomarkers. Until now, research has focused on the highly abundant urinary proteins and peptides, but analysis of the less abundant and naturally existing urinary proteins and peptides still remains a challenge. In conclusion, urine has evolved as one of the most attractive body fluids in clinical proteomics with potentially a rapid application in the clinic.